diff --git a/package.json b/package.json
index f942035..bf91f85 100644
--- a/package.json
+++ b/package.json
@@ -1,7 +1,7 @@
 {
   "name": "kimiswitch",
   "private": true,
-  "version": "0.7.17",
+  "version": "0.7.18",
   "type": "module",
   "scripts": {
     "dev": "vite",
diff --git a/release-notes-v0.7.18.md b/release-notes-v0.7.18.md
new file mode 100644
index 0000000..fe1219b
--- /dev/null
+++ b/release-notes-v0.7.18.md
@@ -0,0 +1,14 @@
+# KimiSwitch v0.7.18
+
+## 新增
+
+- **会话管理「一键归档」**：支持按 1 个月前 / 半个月前 / 1 星期前 / 指定日期，一键归档所有最后活跃时间早于所选时间点的会话（一次批量操作，替代逐个选择）；结果反馈已归档 / 跳过数量
+- **归档用量快照落库**：归档瞬间把每个会话的 token 用量与费用按「天 × 模型」粒度快照进 SQLite（`archived_sessions` 表）。之后删除已归档会话（释放磁盘）不再损失历史统计——仪表盘的趋势图、热力图、模型统计、区间合计均会自动合并快照数据，且与现存文件实时统计严格去重（只合并文件已删除的归档会话，绝不双计）
+
+## 修复
+
+- models-dev 快照同步至 2026-09-14（7784 模型 / 213 供应商），`public/` 前端静态目录同步；pricing 测试价格断言跟随 DeepSeek 官方调价（deepseek-v4-flash input 0.14→0.15 / output 0.28→0.60）
+
+## 备注
+
+- 归档仍是元数据语义（文件原地保留），删除文件才会触发快照合并；用量配置、账单查询等其余功能不受影响
diff --git a/src-tauri/Cargo.lock b/src-tauri/Cargo.lock
index 2f9eb6a..c3d62e7 100644
--- a/src-tauri/Cargo.lock
+++ b/src-tauri/Cargo.lock
@@ -1978,7 +1978,7 @@ dependencies = [
 
 [[package]]
 name = "kimiswitch"
-version = "0.7.17"
+version = "0.7.18"
 dependencies = [
  "anyhow",
  "chrono",
diff --git a/src-tauri/Cargo.toml b/src-tauri/Cargo.toml
index 855154b..cc3e019 100644
--- a/src-tauri/Cargo.toml
+++ b/src-tauri/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "kimiswitch"
-version = "0.7.17"
+version = "0.7.18"
 description = "Kimi Switch - model config manager"
 authors = ["codingplan.site"]
 edition = "2021"
diff --git a/src-tauri/src/dashboard.rs b/src-tauri/src/dashboard.rs
index 6eec106..4ceabf8 100644
--- a/src-tauri/src/dashboard.rs
+++ b/src-tauri/src/dashboard.rs
@@ -1,4 +1,5 @@
 use chrono::{DateTime, Datelike, Local, TimeZone};
+use crate::db::{ArchivedSessionSnapshot, DayModelStat, DayStat};
 use regex::Regex;
 use serde::{Deserialize, Serialize};
 use std::collections::HashMap;
@@ -277,6 +278,15 @@ pub struct ActionResponse {
     pub deleted: Option<bool>,
 }
 
+/// Outcome of the bulk "archive everything older than X" command.
+#[derive(Debug, Serialize, Deserialize, Clone)]
+#[serde(rename_all = "camelCase")]
+pub struct BulkArchiveResult {
+    pub archived: usize,
+    pub skipped: usize,
+    pub errors: Vec<String>,
+}
+
 #[derive(Debug, Serialize, Deserialize, Clone)]
 #[serde(rename_all = "camelCase")]
 pub struct PreviewResult {
@@ -853,67 +863,8 @@ fn scan_usage(home: &Path) -> (Vec<UsageRecord>, ScanMeta) {
             Ok(c) => c,
             Err(_) => continue,
         };
-        for line in content.lines() {
-            lines_seen += 1;
-            if !line.contains("\"usage.record\"") { continue; }
-            let obj: serde_json::Value = match serde_json::from_str(line) {
-                Ok(v) => v,
-                Err(_) => continue,
-            };
-            if obj.get("type").and_then(|v| v.as_str()) != Some("usage.record") { continue; }
-            let scope = obj.get("usageScope").and_then(|v| v.as_str()).unwrap_or("turn");
-            if scope != "turn" { continue; }
-
-            let model_raw = obj.get("model").and_then(|v| v.as_str()).unwrap_or("unknown").to_string();
-            // Kimi Code writes the internal marker `__secondary__` as the model
-            // key for usage records emitted by subagents bound to the
-            // configured secondary model. The record stays keyed on that
-            // stable marker so historical records keep their semantics if the
-            // secondary config changes later; cost billing follows the
-            // currently configured secondary model, and the record is flagged
-            // is_secondary so the UI shows it as its own "subagent model"
-            // entry.
-            let is_secondary = model_raw == "__secondary__";
-            let from_env = model_raw == "__kimi_env_model__";
-            let price_model = if is_secondary {
-                secondary_alias.clone().unwrap_or_else(|| model_raw.clone())
-            } else {
-                model_raw.clone()
-            };
-            let time = obj.get("time").and_then(|v| v.as_u64()).unwrap_or(0);
-            let usage = &obj["usage"];
-            let input_other = usage.get("inputOther").and_then(|v| v.as_u64()).unwrap_or(0);
-            let output = usage.get("output").and_then(|v| v.as_u64()).unwrap_or(0);
-            let cache_read = usage.get("inputCacheRead").and_then(|v| v.as_u64()).unwrap_or(0);
-            let cache_create = usage.get("inputCacheCreation").and_then(|v| v.as_u64()).unwrap_or(0);
-
-            // Resolve model display
-            let bare = model_raw.rsplit_once('/').map(|x| x.1).unwrap_or(&model_raw);
-            let (cost, est) = cost_for_usage(input_other, output, cache_read, cache_create, &price_model);
-            // Subagent records are inherently estimates: the `__secondary__`
-            // marker carries no model identity, so the cost is flagged as
-            // estimated even when the current secondary config resolves to a
-            // priced listing.
-            let est = est || is_secondary;
-            let (pid, _ch, _ip, _op, _) = match_price(&price_model);
-
-            records.push(UsageRecord {
-                time,
-                model: model_raw.clone(),
-                model_resolved: bare.to_string(),
-                model_display: model_raw.clone(),
-                provider: resolve_provider(&price_model, &alias2prov),
-                from_env,
-                is_secondary,
-                input_other,
-                output,
-                input_cache_read: cache_read,
-                input_cache_creation: cache_create,
-                cost_usd: cost,
-                cost_estimated: est,
-                price_id: pid,
-            });
-        }
+        lines_seen += content.lines().count();
+        records.extend(parse_wire_usage_records(&content, &secondary_alias, &alias2prov));
     }
 
     records.sort_by(|a, b| b.time.cmp(&a.time));
@@ -926,6 +877,180 @@ fn scan_usage(home: &Path) -> (Vec<UsageRecord>, ScanMeta) {
     })
 }
 
+/// Parse one `wire.jsonl` body into usage records. Extracted from
+/// `scan_usage` so a single session can be snapshotted without walking the
+/// whole sessions tree; the record filter chain is unchanged.
+fn parse_wire_usage_records(
+    content: &str,
+    secondary_alias: &Option<String>,
+    alias2prov: &HashMap<String, String>,
+) -> Vec<UsageRecord> {
+    let mut records = Vec::new();
+    for line in content.lines() {
+        if !line.contains("\"usage.record\"") { continue; }
+        let obj: serde_json::Value = match serde_json::from_str(line) {
+            Ok(v) => v,
+            Err(_) => continue,
+        };
+        if obj.get("type").and_then(|v| v.as_str()) != Some("usage.record") { continue; }
+        let scope = obj.get("usageScope").and_then(|v| v.as_str()).unwrap_or("turn");
+        if scope != "turn" { continue; }
+
+        let model_raw = obj.get("model").and_then(|v| v.as_str()).unwrap_or("unknown").to_string();
+        // Kimi Code writes the internal marker `__secondary__` as the model
+        // key for usage records emitted by subagents bound to the
+        // configured secondary model. The record stays keyed on that
+        // stable marker so historical records keep their semantics if the
+        // secondary config changes later; cost billing follows the
+        // currently configured secondary model, and the record is flagged
+        // is_secondary so the UI shows it as its own "subagent model"
+        // entry.
+        let is_secondary = model_raw == "__secondary__";
+        let from_env = model_raw == "__kimi_env_model__";
+        let price_model = if is_secondary {
+            secondary_alias.clone().unwrap_or_else(|| model_raw.clone())
+        } else {
+            model_raw.clone()
+        };
+        let time = obj.get("time").and_then(|v| v.as_u64()).unwrap_or(0);
+        let usage = &obj["usage"];
+        let input_other = usage.get("inputOther").and_then(|v| v.as_u64()).unwrap_or(0);
+        let output = usage.get("output").and_then(|v| v.as_u64()).unwrap_or(0);
+        let cache_read = usage.get("inputCacheRead").and_then(|v| v.as_u64()).unwrap_or(0);
+        let cache_create = usage.get("inputCacheCreation").and_then(|v| v.as_u64()).unwrap_or(0);
+
+        // Resolve model display
+        let bare = model_raw.rsplit_once('/').map(|x| x.1).unwrap_or(&model_raw);
+        let (cost, est) = cost_for_usage(input_other, output, cache_read, cache_create, &price_model);
+        // Subagent records are inherently estimates: the `__secondary__`
+        // marker carries no model identity, so the cost is flagged as
+        // estimated even when the current secondary config resolves to a
+        // priced listing.
+        let est = est || is_secondary;
+        let (pid, _ch, _ip, _op, _) = match_price(&price_model);
+
+        records.push(UsageRecord {
+            time,
+            model: model_raw.clone(),
+            model_resolved: bare.to_string(),
+            model_display: model_raw.clone(),
+            provider: resolve_provider(&price_model, &alias2prov),
+            from_env,
+            is_secondary,
+            input_other,
+            output,
+            input_cache_read: cache_read,
+            input_cache_creation: cache_create,
+            cost_usd: cost,
+            cost_estimated: est,
+            price_id: pid,
+        });
+    }
+    records
+}
+
+/// Aggregate raw usage records into the per-day, per-model snapshot stored
+/// for an archived session.
+fn snapshot_from_records(records: &[UsageRecord]) -> Vec<DayStat> {
+    let mut by_day: HashMap<String, (u64, HashMap<String, DayModelStat>)> = HashMap::new();
+    for r in records {
+        let entry = by_day
+            .entry(day_key(r.time))
+            .or_insert_with(|| (local_midnight_ms(r.time, 0), HashMap::new()));
+        let m = entry.1.entry(r.model.clone()).or_insert_with(|| DayModelStat {
+            model: r.model.clone(),
+            requests: 0,
+            input_other: 0,
+            output: 0,
+            input_cache_read: 0,
+            input_cache_creation: 0,
+            cost_usd: 0.0,
+        });
+        m.requests += 1;
+        m.input_other += r.input_other;
+        m.output += r.output;
+        m.input_cache_read += r.input_cache_read;
+        m.input_cache_creation += r.input_cache_creation;
+        m.cost_usd += r.cost_usd;
+    }
+    let mut days: Vec<DayStat> = by_day
+        .into_iter()
+        .map(|(day, (day_start_ms, models))| {
+            let mut models: Vec<DayModelStat> = models.into_values().collect();
+            models.sort_by(|a, b| a.model.cmp(&b.model));
+            DayStat { day, day_start_ms, models }
+        })
+        .collect();
+    days.sort_by(|a, b| a.day.cmp(&b.day));
+    days
+}
+
+/// Synthesize usage records from stored archive snapshots. Only snapshots
+/// whose session directory is gone are synthesized: sessions still on disk
+/// are covered by the live wire.jsonl scan, and emitting both would double
+/// count their usage.
+fn synthesize_snapshot_records(rows: &[ArchivedSessionSnapshot], home: &Path) -> Vec<UsageRecord> {
+    let root = sessions_root(home);
+    let legacy_root = root.join(".kcd-archive");
+    let alias2prov = build_alias_provider_map(home);
+    let secondary_alias = read_secondary_model_alias(home);
+    let mut out = Vec::new();
+    for row in rows {
+        if root.join(&row.workspace_id).join(&row.session_id).exists() { continue; }
+        if legacy_root.join(&row.workspace_id).join(&row.session_id).exists() { continue; }
+        for day in &row.day_stats {
+            for m in &day.models {
+                let is_secondary = m.model == "__secondary__";
+                let price_model = if is_secondary {
+                    secondary_alias.clone().unwrap_or_else(|| m.model.clone())
+                } else {
+                    m.model.clone()
+                };
+                let bare = m.model.rsplit_once('/').map(|x| x.1).unwrap_or(&m.model).to_string();
+                out.push(UsageRecord {
+                    time: day.day_start_ms,
+                    model: m.model.clone(),
+                    model_resolved: bare,
+                    model_display: m.model.clone(),
+                    provider: resolve_provider(&price_model, &alias2prov),
+                    from_env: m.model == "__kimi_env_model__",
+                    is_secondary,
+                    input_other: m.input_other,
+                    output: m.output,
+                    input_cache_read: m.input_cache_read,
+                    input_cache_creation: m.input_cache_creation,
+                    cost_usd: m.cost_usd,
+                    cost_estimated: true,
+                    price_id: String::new(),
+                });
+            }
+        }
+    }
+    out
+}
+
+/// Append the synthesized records for `rows` to a live scan result and
+/// restore the newest-first ordering `scan_usage` produces.
+fn merge_snapshot_records(
+    mut records: Vec<UsageRecord>,
+    rows: &[ArchivedSessionSnapshot],
+    home: &Path,
+) -> Vec<UsageRecord> {
+    // Nothing archived yet: keep the scan result untouched (and skip the
+    // config reads the synthesis would do).
+    if rows.is_empty() { return records; }
+    records.extend(synthesize_snapshot_records(rows, home));
+    records.sort_by(|a, b| b.time.cmp(&a.time));
+    records
+}
+
+/// Live scan records plus the stored usage of archived sessions whose files
+/// have been deleted, so dashboard stats survive session deletion.
+fn records_with_archive_merge(home: &Path, records: Vec<UsageRecord>) -> Vec<UsageRecord> {
+    let rows = crate::db::list_archived_sessions().unwrap_or_default();
+    merge_snapshot_records(records, &rows, home)
+}
+
 // ---------------------------------------------------------------------------
 // Scan cache
 // ---------------------------------------------------------------------------
@@ -1332,6 +1457,147 @@ fn set_session_archived_meta(session_dir: &Path, archived: bool) -> Result<(), S
     Ok(())
 }
 
+/// Parse a `state.json` timestamp into epoch ms. kimi-code writes epoch-ms
+/// numbers, other builds write ISO-8601 strings — accept both, plus numeric
+/// strings.
+fn parse_state_time_ms(value: &serde_json::Value) -> Option<u64> {
+    match value {
+        serde_json::Value::Number(n) => n.as_u64().or_else(|| n.as_f64().map(|f| f.max(0.0) as u64)),
+        serde_json::Value::String(s) => parse_time_string_ms(s),
+        _ => None,
+    }
+}
+
+fn parse_time_string_ms(s: &str) -> Option<u64> {
+    let t = s.trim();
+    if t.is_empty() { return None; }
+    if let Ok(n) = t.parse::<u64>() {
+        // Numeric string: epoch ms when it is already millisecond-sized.
+        return Some(if n >= 1e12 as u64 { n } else { n * 1000 });
+    }
+    if let Ok(dt) = DateTime::parse_from_rfc3339(t) {
+        return Some(dt.timestamp_millis().max(0) as u64);
+    }
+    for fmt in [
+        "%Y-%m-%dT%H:%M:%S%.f",
+        "%Y-%m-%dT%H:%M:%S",
+        "%Y-%m-%d %H:%M:%S%.f",
+        "%Y-%m-%d %H:%M:%S",
+    ] {
+        if let Ok(naive) = chrono::NaiveDateTime::parse_from_str(t, fmt) {
+            return Some(naive.and_utc().timestamp_millis().max(0) as u64);
+        }
+    }
+    None
+}
+
+/// Read a session's `state.json` as a JSON object (None when missing or
+/// unparseable).
+fn read_state_obj(session_dir: &Path) -> Option<serde_json::Value> {
+    let content = fs::read_to_string(session_dir.join("state.json")).ok()?;
+    let obj: serde_json::Value = serde_json::from_str(&content).ok()?;
+    if obj.is_object() { Some(obj) } else { None }
+}
+
+/// Session directory mtime in epoch ms — the fallback when `state.json` has
+/// no parseable `updatedAt`.
+fn dir_mtime_ms(dir: &Path) -> Option<u64> {
+    dir.metadata().ok().and_then(|m| m.modified().ok())
+        .and_then(|t| t.duration_since(std::time::UNIX_EPOCH).ok())
+        .map(|d| d.as_millis() as u64)
+}
+
+/// Usage records of one session: every `wire.jsonl` below its directory
+/// (agent subdirectories included), with the same blob/task filtering the
+/// full-tree scan applies.
+fn parse_session_wire_usage(
+    dir: &Path,
+    secondary_alias: &Option<String>,
+    alias2prov: &HashMap<String, String>,
+) -> Vec<UsageRecord> {
+    let mut records = Vec::new();
+    for entry in WalkDir::new(dir).into_iter().filter_map(|e| e.ok()) {
+        if entry.file_name() != "wire.jsonl" || !entry.file_type().is_file() { continue; }
+        let p = entry.path();
+        if p.to_string_lossy().contains("blobs") || p.to_string_lossy().contains("tasks") { continue; }
+        let Ok(content) = fs::read_to_string(p) else { continue };
+        records.extend(parse_wire_usage_records(&content, secondary_alias, alias2prov));
+    }
+    records
+}
+
+/// Bulk-archive every active session whose last activity predates `cutoff_ms`
+/// (epoch ms) and store a usage snapshot per session in SQLite, so dashboard
+/// stats keep counting their history after the directories are deleted.
+/// Sessions already archived, in `.kcd-archive`, or without a readable
+/// `state.json` are left alone.
+fn archive_sessions_before_cmd(home: &Path, cutoff_ms: u64) -> BulkArchiveResult {
+    let root = sessions_root(home);
+    let alias2prov = build_alias_provider_map(home);
+    let secondary_alias = read_secondary_model_alias(home);
+    let now_ms = std::time::SystemTime::now()
+        .duration_since(std::time::UNIX_EPOCH).unwrap_or_default().as_millis() as u64;
+    let mut result = BulkArchiveResult { archived: 0, skipped: 0, errors: Vec::new() };
+
+    for wid in list_workspace_dirs(home) {
+        for entry in safe_read_dir(&root.join(&wid)) {
+            if !entry.file_type().map(|t| t.is_dir()).unwrap_or(false) { continue; }
+            let sid = entry.file_name().to_string_lossy().to_string();
+            if !session_re().is_match(&sid) { continue; }
+            let dir = entry.path();
+            let Some(state) = read_state_obj(&dir) else {
+                result.skipped += 1;
+                continue;
+            };
+            if state.get("archived").and_then(|v| v.as_bool()).unwrap_or(false) { continue; }
+            let Some(updated_ms) = state
+                .get("updatedAt")
+                .and_then(parse_state_time_ms)
+                .or_else(|| dir_mtime_ms(&dir))
+            else {
+                result.skipped += 1;
+                continue;
+            };
+            if updated_ms >= cutoff_ms {
+                result.skipped += 1;
+                continue;
+            }
+
+            if let Err(e) = set_session_archived_meta(&dir, true) {
+                result.errors.push(format!("{wid}/{sid}: {e}"));
+                continue;
+            }
+            let day_stats = snapshot_from_records(&parse_session_wire_usage(
+                &dir, &secondary_alias, &alias2prov,
+            ));
+            let mut total_tokens = 0u64;
+            let mut total_cost_usd = 0.0f64;
+            for day in &day_stats {
+                for m in &day.models {
+                    total_tokens += m.input_other + m.output + m.input_cache_read + m.input_cache_creation;
+                    total_cost_usd += m.cost_usd;
+                }
+            }
+            let snapshot = ArchivedSessionSnapshot {
+                session_id: sid.clone(),
+                workspace_id: wid.clone(),
+                title: state.get("title").and_then(|v| v.as_str()).map(|s| s.to_string()),
+                archived_at_ms: now_ms,
+                updated_at_ms: Some(updated_ms),
+                created_at_ms: state.get("createdAt").and_then(parse_state_time_ms),
+                total_tokens,
+                total_cost_usd,
+                day_stats,
+            };
+            result.archived += 1;
+            if let Err(e) = crate::db::upsert_archived_session(&snapshot) {
+                result.errors.push(format!("{wid}/{sid}: snapshot: {e}"));
+            }
+        }
+    }
+    result
+}
+
 fn humanize_workspace(id: &str) -> String {
     let re = Regex::new(r"^wd_(.+)_[0-9a-fA-F]{8,}$").unwrap();
     if let Some(caps) = re.captures(id) {
@@ -1876,6 +2142,7 @@ pub fn get_summary(home_override: Option<String>, range: Option<String>, refresh
     let r = range.unwrap_or_else(|| "30d".into());
 
     let (records, meta) = scan_usage_cached(&home, refresh);
+    let records = records_with_archive_merge(&home, records);
     let t1 = std::time::Instant::now();
     let stats = aggregate(&records, &r, now_ms);
     let all_stats = aggregate(&records, "all", now_ms);
@@ -1983,6 +2250,7 @@ fn build_day_detail(date: &str, records: &[UsageRecord]) -> Option<DailyRow> {
 pub fn get_day_detail(home_override: Option<String>, date: String) -> Option<DailyRow> {
     let home = resolve_kimi_home(home_override);
     let (records, _) = scan_usage_cached(&home, false);
+    let records = records_with_archive_merge(&home, records);
     build_day_detail(&date, &records)
 }
 
@@ -1998,6 +2266,14 @@ pub fn archive_session(home_override: Option<String>, workspace_id: String, sess
     archive_session_cmd(&home, &workspace_id, &session_id)
 }
 
+/// Bulk-archive every active session whose last activity predates `cutoff_ms`
+/// (epoch ms) across all workspaces, storing a usage snapshot per session.
+#[tauri::command]
+pub fn archive_sessions_before(home_override: Option<String>, cutoff_ms: u64) -> BulkArchiveResult {
+    let home = resolve_kimi_home(home_override);
+    archive_sessions_before_cmd(&home, cutoff_ms)
+}
+
 #[tauri::command]
 pub fn unarchive_session(home_override: Option<String>, workspace_id: String, session_id: String) -> Result<ActionResponse, String> {
     let home = resolve_kimi_home(home_override);
@@ -2073,8 +2349,8 @@ mod pricing_tests {
         let (id, _, input, output, est) = match_price("CodingPlan.site/deepseek-v4-flash");
         assert!(!est, "resolved via models.dev, not estimated");
         assert_eq!(id, "deepseek/deepseek-v4-flash");
-        assert_eq!(input, 0.14);
-        assert_eq!(output, 0.28);
+        assert_eq!(input, 0.15);
+        assert_eq!(output, 0.6);
     }
 
     #[test]
@@ -2432,3 +2708,271 @@ mod range_and_model_totals_tests {
         assert_eq!(total, 3 * 200);
     }
 }
+
+#[cfg(test)]
+mod archive_snapshot_tests {
+    use super::*;
+
+    const WID: &str = "wd_proj_a1b2c3d4e5f6";
+    const LIVE_SID: &str = "session_11111111-2222-3333-4444-555555555555";
+    const GONE_SID: &str = "session_99999999-8888-7777-6666-555555555555";
+
+    fn now_ms() -> u64 {
+        std::time::SystemTime::now()
+            .duration_since(std::time::UNIX_EPOCH).unwrap().as_millis() as u64
+    }
+
+    fn rec(time: u64, model: &str, tokens: (u64, u64, u64, u64), cost: f64) -> UsageRecord {
+        UsageRecord {
+            time,
+            model: model.to_string(),
+            input_other: tokens.0,
+            output: tokens.1,
+            input_cache_read: tokens.2,
+            input_cache_creation: tokens.3,
+            cost_usd: cost,
+            cost_estimated: false,
+            price_id: String::new(),
+            model_resolved: model.rsplit_once('/').map(|x| x.1).unwrap_or(model).to_string(),
+            model_display: model.to_string(),
+            provider: None,
+            from_env: false,
+            is_secondary: false,
+        }
+    }
+
+    fn snapshot_row(
+        sid: &str,
+        day_start_ms: u64,
+        model: &str,
+        tokens: u64,
+    ) -> ArchivedSessionSnapshot {
+        ArchivedSessionSnapshot {
+            session_id: sid.to_string(),
+            workspace_id: WID.to_string(),
+            title: None,
+            archived_at_ms: 0,
+            updated_at_ms: None,
+            created_at_ms: None,
+            total_tokens: tokens,
+            total_cost_usd: 0.0,
+            day_stats: vec![DayStat {
+                day: day_key(day_start_ms),
+                day_start_ms,
+                models: vec![DayModelStat {
+                    model: model.to_string(),
+                    requests: 2,
+                    input_other: tokens,
+                    output: 0,
+                    input_cache_read: 0,
+                    input_cache_creation: 0,
+                    cost_usd: 1.5,
+                }],
+            }],
+        }
+    }
+
+    fn write_state(dir: &Path, updated_ms: u64, archived: bool) {
+        let state = serde_json::json!({
+            "id": dir.file_name().unwrap().to_string_lossy(),
+            "createdAt": updated_ms,
+            "updatedAt": updated_ms,
+            "archived": archived,
+            "title": "archived candidate",
+        });
+        fs::write(dir.join("state.json"), state.to_string()).unwrap();
+    }
+
+    fn read_state(dir: &Path) -> serde_json::Value {
+        serde_json::from_str(&fs::read_to_string(dir.join("state.json")).unwrap()).unwrap()
+    }
+
+    #[test]
+    fn snapshot_groups_records_by_local_day_and_model() {
+        let now = now_ms();
+        let d1 = local_midnight_ms(now, 2);
+        let d2 = local_midnight_ms(now, 1);
+        let records = vec![
+            rec(d1 + 3_600_000, "openai/gpt-x", (100, 10, 5, 1), 0.5),
+            rec(d1 + 7_200_000, "openai/gpt-x", (200, 20, 0, 0), 0.25),
+            rec(d1 + 60_000, "moonshotai/kimi-k3", (1, 2, 3, 4), 0.01),
+            rec(d2 + 1_000, "openai/gpt-x", (7, 7, 7, 7), 0.07),
+        ];
+        let days = snapshot_from_records(&records);
+        assert_eq!(days.len(), 2, "one bucket per local day");
+
+        let first = &days[0];
+        assert_eq!(first.day, day_key(d1));
+        assert_eq!(first.day_start_ms, d1, "day bucket starts at local midnight");
+        assert_eq!(first.models.len(), 2);
+        let gpt = first.models.iter().find(|m| m.model == "openai/gpt-x").unwrap();
+        assert_eq!(gpt.requests, 2);
+        assert_eq!(gpt.input_other, 300);
+        assert_eq!(gpt.output, 30);
+        assert_eq!(gpt.input_cache_read, 5);
+        assert_eq!(gpt.input_cache_creation, 1);
+        assert_eq!(gpt.cost_usd, 0.75);
+        // Deterministic ordering: models sorted by raw model key.
+        assert_eq!(first.models[0].model, "moonshotai/kimi-k3");
+
+        assert_eq!(days[1].day, day_key(d2));
+        assert_eq!(days[1].day_start_ms, d2);
+        assert_eq!(days[1].models.len(), 1);
+        assert_eq!(days[1].models[0].input_other, 7);
+    }
+
+    #[test]
+    fn synthesize_only_covers_sessions_whose_files_are_gone() {
+        let td = tempfile::tempdir().unwrap();
+        let home = td.path().join("home");
+        fs::create_dir_all(home.join("sessions").join(WID).join(LIVE_SID)).unwrap();
+
+        let day_start = 1_700_000_000_000u64;
+        let rows = vec![
+            snapshot_row(LIVE_SID, day_start, "openai/gpt-x", 100),
+            snapshot_row(GONE_SID, day_start, "openai/gpt-x", 200),
+        ];
+        let out = synthesize_snapshot_records(&rows, &home);
+        assert_eq!(out.len(), 1, "live session dirs stay with the live scan");
+
+        let r = &out[0];
+        assert_eq!(r.time, day_start);
+        assert_eq!(r.model, "openai/gpt-x");
+        assert_eq!(r.model_resolved, "gpt-x");
+        assert_eq!(r.model_display, "openai/gpt-x");
+        assert_eq!(r.provider.as_deref(), Some("openai"));
+        assert_eq!(r.input_other, 200);
+        assert_eq!(r.cost_usd, 1.5);
+        assert!(r.cost_estimated, "snapshot costs are estimates");
+        assert_eq!(r.price_id, "");
+        assert!(!r.is_secondary);
+        assert!(!r.from_env);
+    }
+
+    #[test]
+    fn merge_appends_missing_sessions_newest_first_without_double_counting() {
+        let td = tempfile::tempdir().unwrap();
+        let home = td.path().join("home");
+        fs::create_dir_all(home.join("sessions").join(WID).join(LIVE_SID)).unwrap();
+
+        let now = now_ms();
+        let old_day = local_midnight_ms(now, 5);
+        let new_day = local_midnight_ms(now, 1);
+        let gone_old = "session_22222222-2222-3333-4444-555555555555";
+        let gone_new = "session_33333333-2222-3333-4444-555555555555";
+        let rows = vec![
+            snapshot_row(LIVE_SID, new_day, "openai/gpt-x", 999),
+            snapshot_row(gone_old, old_day, "openai/gpt-x", 10),
+            snapshot_row(gone_new, new_day, "openai/gpt-x", 20),
+        ];
+        let live = vec![rec(new_day + 5_000, "openai/gpt-x", (1, 1, 1, 1), 0.01)];
+        let merged = merge_snapshot_records(live, &rows, &home);
+
+        assert_eq!(merged.len(), 3, "live record plus the two missing sessions");
+        assert_eq!(merged[0].time, new_day + 5_000, "newest record first");
+        assert_eq!(merged[1].time, new_day);
+        assert_eq!(merged[2].time, old_day);
+        assert_eq!(merged[1].input_other, 20);
+        assert_eq!(merged[2].input_other, 10);
+        assert!(
+            merged.iter().all(|r| r.input_other != 999),
+            "a live session's stored snapshot must never be synthesized"
+        );
+    }
+
+    #[test]
+    fn state_times_parse_epoch_numbers_and_iso_strings() {
+        assert_eq!(
+            parse_state_time_ms(&serde_json::json!(1_700_000_000_000u64)),
+            Some(1_700_000_000_000)
+        );
+        assert_eq!(
+            parse_state_time_ms(&serde_json::json!("1700000000000")),
+            Some(1_700_000_000_000)
+        );
+        assert_eq!(
+            parse_state_time_ms(&serde_json::json!("2025-01-02T03:04:05.000Z")),
+            Some(1_735_787_045_000)
+        );
+        assert_eq!(
+            parse_state_time_ms(&serde_json::json!("2025-01-02T03:04:05")),
+            Some(1_735_787_045_000)
+        );
+        assert_eq!(
+            parse_state_time_ms(&serde_json::json!("2025-01-02 03:04:05")),
+            Some(1_735_787_045_000)
+        );
+        assert_eq!(parse_state_time_ms(&serde_json::json!(null)), None);
+        assert_eq!(parse_state_time_ms(&serde_json::json!("not-a-date")), None);
+    }
+
+    #[test]
+    fn bulk_archive_flags_old_sessions_and_snapshots_their_usage() {
+        let td = tempfile::tempdir().unwrap();
+        let home = td.path().join("home");
+        // Redirect the SQLite store so the test never touches the user's DB.
+        std::env::set_var("KIMI_SWITCH_DB_PATH", td.path().join("test.db"));
+
+        let ws = home.join("sessions").join(WID);
+        let now = now_ms();
+        let old_ms = now - 60 * 24 * 3600 * 1000;
+
+        let old_dir = ws.join(LIVE_SID);
+        fs::create_dir_all(&old_dir).unwrap();
+        write_state(&old_dir, old_ms, false);
+        let wire = serde_json::json!({
+            "type": "usage.record",
+            "usageScope": "turn",
+            "time": old_ms,
+            "model": "openai/gpt-x",
+            "usage": {
+                "inputOther": 100,
+                "output": 50,
+                "inputCacheRead": 10,
+                "inputCacheCreation": 5,
+            },
+        });
+        fs::write(old_dir.join("wire.jsonl"), format!("{wire}\n")).unwrap();
+
+        let new_sid = "session_44444444-2222-3333-4444-555555555555";
+        let new_dir = ws.join(new_sid);
+        fs::create_dir_all(&new_dir).unwrap();
+        write_state(&new_dir, now - 3_600_000, false);
+
+        let cutoff = now - 30 * 24 * 3600 * 1000;
+        let res = archive_sessions_before_cmd(&home, cutoff);
+        assert_eq!(res.archived, 1, "only the stale session is archived");
+        assert_eq!(res.skipped, 1, "the recent session is reported as skipped");
+        assert!(res.errors.is_empty(), "{:?}", res.errors);
+
+        // Metadata archive happened in place, the recent session is untouched.
+        assert_eq!(read_state(&old_dir)["archived"], true);
+        assert!(read_state(&old_dir)["archivedAt"].as_u64().unwrap() > 0);
+        assert_eq!(read_state(&new_dir)["archived"], false);
+
+        // Usage snapshot landed in SQLite with the session's totals.
+        let rows = crate::db::list_archived_sessions().unwrap();
+        let row = rows.iter().find(|r| r.session_id == LIVE_SID).expect("snapshot row");
+        assert_eq!(row.workspace_id, WID);
+        assert_eq!(row.title.as_deref(), Some("archived candidate"));
+        assert_eq!(row.updated_at_ms, Some(old_ms));
+        assert_eq!(row.total_tokens, 165);
+        assert!(row.total_cost_usd > 0.0);
+        assert_eq!(row.day_stats.len(), 1);
+        assert_eq!(row.day_stats[0].day, day_key(old_ms));
+        assert_eq!(row.day_stats[0].models[0].requests, 1);
+        assert_eq!(row.day_stats[0].models[0].input_other, 100);
+
+        // While the files are still there, the live scan owns the usage.
+        let merged = records_with_archive_merge(&home, vec![]);
+        assert!(merged.is_empty(), "no synthesized records while the dir exists");
+
+        // Once the archived directory is deleted, stats come from the snapshot.
+        fs::remove_dir_all(&old_dir).unwrap();
+        let merged = records_with_archive_merge(&home, vec![]);
+        assert_eq!(merged.len(), 1);
+        assert_eq!(merged[0].input_other, 100);
+        assert_eq!(merged[0].output, 50);
+        assert_eq!(day_key(merged[0].time), day_key(old_ms));
+    }
+}
diff --git a/src-tauri/src/db.rs b/src-tauri/src/db.rs
index 445b07b..4ccaca8 100644
--- a/src-tauri/src/db.rs
+++ b/src-tauri/src/db.rs
@@ -10,6 +10,7 @@ use std::path::PathBuf;
 use anyhow::Context;
 use indexmap::IndexMap;
 use rusqlite::{params, Connection};
+use serde::{Deserialize, Serialize};
 use serde_json::Value;
 
 use crate::models::{Agent, Config, Model, Provider, ProviderType};
@@ -23,6 +24,13 @@ pub fn kimi_switch_data_dir() -> PathBuf {
 }
 
 pub fn db_path() -> PathBuf {
+    // Tests (and power users) can point the store elsewhere; production always
+    // resolves to the default location under the home directory.
+    if let Some(p) = std::env::var_os("KIMI_SWITCH_DB_PATH") {
+        if !p.is_empty() {
+            return PathBuf::from(p);
+        }
+    }
     kimi_switch_data_dir().join("kimi-switch.db")
 }
 
@@ -31,6 +39,10 @@ pub fn db_path() -> PathBuf {
 /// configuration. Safe to call on every startup — it is a no-op once the new
 /// directory exists.
 fn migrate_legacy_data_dir() {
+    // A redirected store (tests) must never touch the real home directory.
+    if std::env::var_os("KIMI_SWITCH_DB_PATH").is_some() {
+        return;
+    }
     let new_dir = kimi_switch_data_dir();
     if new_dir.exists() {
         return;
@@ -106,6 +118,24 @@ pub fn init_db() -> DbResult<Connection> {
         [],
     )?;
 
+    // Usage snapshots taken when sessions are bulk-archived: keep the session's
+    // token/cost history queryable after its directory (and wire.jsonl) is
+    // deleted from disk.
+    conn.execute(
+        "CREATE TABLE IF NOT EXISTS archived_sessions (
+            session_id     TEXT PRIMARY KEY,
+            workspace_id   TEXT NOT NULL,
+            title          TEXT,
+            archived_at_ms INTEGER NOT NULL,
+            updated_at_ms  INTEGER,
+            created_at_ms  INTEGER,
+            total_tokens   INTEGER NOT NULL DEFAULT 0,
+            total_cost_usd REAL NOT NULL DEFAULT 0,
+            day_stats      TEXT NOT NULL DEFAULT '[]'
+        )",
+        [],
+    )?;
+
     // Add icon columns for provider icon picker (introduced in v0.3.1).
     // SQLite has no ADD COLUMN IF NOT EXISTS, so ignore duplicate-column errors.
     for stmt in [
@@ -330,6 +360,104 @@ pub fn delete_setting_pub(key: &str) -> DbResult<()> {
     Ok(())
 }
 
+// ---------------------------------------------------------------------------
+// Archived-session usage snapshots
+// ---------------------------------------------------------------------------
+
+/// Per-model usage totals for one calendar day of an archived session.
+#[derive(Debug, Clone, Serialize, Deserialize)]
+#[serde(rename_all = "camelCase")]
+pub struct DayModelStat {
+    /// Raw model key as written to wire.jsonl (`__secondary__` kept verbatim).
+    pub model: String,
+    pub requests: u64,
+    pub input_other: u64,
+    pub output: u64,
+    pub input_cache_read: u64,
+    pub input_cache_creation: u64,
+    pub cost_usd: f64,
+}
+
+/// One day's per-model usage, stored as JSON in `archived_sessions.day_stats`.
+#[derive(Debug, Clone, Serialize, Deserialize)]
+#[serde(rename_all = "camelCase")]
+pub struct DayStat {
+    /// Local calendar day, `YYYY-MM-DD`.
+    pub day: String,
+    /// Local midnight of `day`, epoch ms — used as the synthesized record time.
+    pub day_start_ms: u64,
+    pub models: Vec<DayModelStat>,
+}
+
+/// Usage snapshot of one session, taken at the moment it is archived.
+#[derive(Debug, Clone, Serialize, Deserialize)]
+#[serde(rename_all = "camelCase")]
+pub struct ArchivedSessionSnapshot {
+    pub session_id: String,
+    pub workspace_id: String,
+    pub title: Option<String>,
+    pub archived_at_ms: u64,
+    pub updated_at_ms: Option<u64>,
+    pub created_at_ms: Option<u64>,
+    pub total_tokens: u64,
+    pub total_cost_usd: f64,
+    pub day_stats: Vec<DayStat>,
+}
+
+/// Insert or replace one archived-session snapshot (keyed by session id, which
+/// is a UUID and never reused).
+pub fn upsert_archived_session(row: &ArchivedSessionSnapshot) -> DbResult<()> {
+    let conn = init_db()?;
+    let day_stats = serde_json::to_string(&row.day_stats)?;
+    conn.execute(
+        "INSERT OR REPLACE INTO archived_sessions
+         (session_id, workspace_id, title, archived_at_ms, updated_at_ms, created_at_ms, total_tokens, total_cost_usd, day_stats)
+         VALUES (?1, ?2, ?3, ?4, ?5, ?6, ?7, ?8, ?9)",
+        params![
+            row.session_id,
+            row.workspace_id,
+            row.title,
+            row.archived_at_ms as i64,
+            row.updated_at_ms.map(|v| v as i64),
+            row.created_at_ms.map(|v| v as i64),
+            row.total_tokens as i64,
+            row.total_cost_usd,
+            day_stats,
+        ],
+    )?;
+    Ok(())
+}
+
+/// Every stored archived-session snapshot. Unreadable `day_stats` JSON degrades
+/// to an empty breakdown instead of failing the whole list.
+pub fn list_archived_sessions() -> DbResult<Vec<ArchivedSessionSnapshot>> {
+    let conn = init_db()?;
+    let mut stmt = conn.prepare(
+        "SELECT session_id, workspace_id, title, archived_at_ms, updated_at_ms, created_at_ms,
+                total_tokens, total_cost_usd, day_stats
+         FROM archived_sessions",
+    )?;
+    let rows = stmt.query_map([], |row| {
+        let day_stats_json: String = row.get(8)?;
+        Ok(ArchivedSessionSnapshot {
+            session_id: row.get(0)?,
+            workspace_id: row.get(1)?,
+            title: row.get(2)?,
+            archived_at_ms: row.get::<_, i64>(3)? as u64,
+            updated_at_ms: row.get::<_, Option<i64>>(4)?.map(|v| v as u64),
+            created_at_ms: row.get::<_, Option<i64>>(5)?.map(|v| v as u64),
+            total_tokens: row.get::<_, i64>(6)? as u64,
+            total_cost_usd: row.get(7)?,
+            day_stats: serde_json::from_str(&day_stats_json).unwrap_or_default(),
+        })
+    })?;
+    let mut out = Vec::new();
+    for row in rows {
+        out.push(row?);
+    }
+    Ok(out)
+}
+
 fn provider_type_for_str(s: &str) -> ProviderType {
     ProviderType::from_kimi_type(s)
 }
diff --git a/src-tauri/src/lib.rs b/src-tauri/src/lib.rs
index 5d31419..cae8669 100644
--- a/src-tauri/src/lib.rs
+++ b/src-tauri/src/lib.rs
@@ -121,6 +121,7 @@ pub fn run() {
             dashboard::get_day_detail,
             dashboard::list_sessions,
             dashboard::archive_session,
+            dashboard::archive_sessions_before,
             dashboard::unarchive_session,
             dashboard::delete_session,
             dashboard::delete_workspace,
diff --git a/src-tauri/tauri.conf.json b/src-tauri/tauri.conf.json
index ad7d478..8d24c59 100644
--- a/src-tauri/tauri.conf.json
+++ b/src-tauri/tauri.conf.json
@@ -1,6 +1,6 @@
 {
   "productName": "Kimi Switch",
-  "version": "0.7.17",
+  "version": "0.7.18",
   "identifier": "com.kimiswitch.app",
   "build": {
     "beforeDevCommand": "npm run dev",
diff --git a/src/components/sessions/SessionsPage.tsx b/src/components/sessions/SessionsPage.tsx
index 2090275..5acf921 100644
--- a/src/components/sessions/SessionsPage.tsx
+++ b/src/components/sessions/SessionsPage.tsx
@@ -1,8 +1,8 @@
-import { useMemo, useState } from "react";
+import { useEffect, useMemo, useState } from "react";
 import { useSessions } from "../../hooks/useSessions";
 import { fmtInt, fmtTime } from "../../lib/dashboard-format";
 import { useTranslation } from "../../i18n";
-import type { SessionRow, WorkspaceRow } from "../../types/sessions";
+import type { BulkArchiveResult, SessionRow, WorkspaceRow } from "../../types/sessions";
 
 function fmtBytes(n: number): string {
   const v = Number(n) || 0;
@@ -23,6 +23,44 @@ function rowKey(row: SessionRow): string {
   return `${row.workspaceId}/${row.id}`;
 }
 
+type ArchiveAllMode = "month" | "half" | "week" | "custom";
+
+type ArchiveAllState = {
+  mode: ArchiveAllMode;
+  /** YYYY-MM-DD, used when mode is "custom". */
+  date: string;
+  busy: boolean;
+  result: BulkArchiveResult | null;
+  error: string | null;
+};
+
+function localDateInput(d: Date): string {
+  const m = String(d.getMonth() + 1).padStart(2, "0");
+  const day = String(d.getDate()).padStart(2, "0");
+  return `${d.getFullYear()}-${m}-${day}`;
+}
+
+/** Today minus one month — the default value of the custom-date picker. */
+function defaultCustomDate(): string {
+  const d = new Date();
+  d.setMonth(d.getMonth() - 1);
+  return localDateInput(d);
+}
+
+/** Cutoff epoch ms for the selected option (custom dates start at local midnight). */
+function cutoffFor(state: ArchiveAllState): number {
+  const now = new Date();
+  if (state.mode === "month" || state.mode === "half" || state.mode === "week") {
+    const d = new Date(now);
+    if (state.mode === "month") d.setMonth(d.getMonth() - 1);
+    if (state.mode === "half") d.setDate(d.getDate() - 15);
+    if (state.mode === "week") d.setDate(d.getDate() - 7);
+    return d.getTime();
+  }
+  const [y, m, day] = state.date.split("-").map(Number);
+  return new Date(y || now.getFullYear(), (m || 1) - 1, day || 1, 0, 0, 0, 0).getTime();
+}
+
 type ConfirmState =
   | { mode: "one"; row: SessionRow }
   | { mode: "bulk"; rows: SessionRow[] }
@@ -52,6 +90,7 @@ export function SessionsPage() {
     refresh,
     archiveSession,
     unarchiveSession,
+    archiveBefore,
     deleteSession,
     deleteWorkspace,
     getPreview,
@@ -62,6 +101,7 @@ export function SessionsPage() {
   const [confirm, setConfirm] = useState<ConfirmState>(null);
   const [confirmBusy, setConfirmBusy] = useState(false);
   const [preview, setPreview] = useState<PreviewState>(null);
+  const [archiveAll, setArchiveAll] = useState<ArchiveAllState | null>(null);
 
   const workspaces = data?.workspaces ?? [];
   const sessions = data?.sessions ?? [];
@@ -199,6 +239,30 @@ export function SessionsPage() {
     0
   );
 
+  useEffect(() => {
+    if (!archiveAll) return;
+    const onKey = (e: KeyboardEvent) => {
+      if (e.key === "Escape") setArchiveAll((s) => (s && s.busy ? s : null));
+    };
+    window.addEventListener("keydown", onKey);
+    return () => window.removeEventListener("keydown", onKey);
+  }, [archiveAll]);
+
+  const runArchiveAll = async () => {
+    if (!archiveAll || archiveAll.busy) return;
+    const cutoffMs = cutoffFor(archiveAll);
+    setArchiveAll((s) => (s ? { ...s, busy: true, result: null, error: null } : s));
+    try {
+      const res = await archiveBefore(cutoffMs);
+      setArchiveAll((s) => (s ? { ...s, busy: false, result: res } : s));
+      setSelected(new Set());
+    } catch (e) {
+      setArchiveAll((s) =>
+        s ? { ...s, busy: false, error: e instanceof Error ? e.message : String(e) } : s
+      );
+    }
+  };
+
   return (
     <div className="flex h-full flex-col overflow-hidden p-4 space-y-3">
       <div className="flex shrink-0 flex-col gap-3 sm:flex-row sm:items-end sm:justify-between">
@@ -376,6 +440,23 @@ export function SessionsPage() {
                   </button>
                 </>
               )}
+              {status !== "archived" && (
+                <button
+                  type="button"
+                  onClick={() =>
+                    setArchiveAll({
+                      mode: "month",
+                      date: defaultCustomDate(),
+                      busy: false,
+                      result: null,
+                      error: null,
+                    })
+                  }
+                  className="px-2 py-1 text-xs rounded border border-border hover:bg-hover-2"
+                >
+                  {t("sessionsArchiveAll")}
+                </button>
+              )}
               <select
                 value={workspace}
                 onChange={(e) => setWorkspace(e.target.value)}
@@ -548,6 +629,112 @@ export function SessionsPage() {
         {data?.home && <>{data.home}</>}
       </div>
 
+      {/* Bulk archive dialog */}
+      {archiveAll && (
+        <div className="fixed inset-0 z-50 flex items-center justify-center bg-black/60 p-4">
+          <div className="w-full max-w-md rounded-xl border border-border bg-panel shadow-xl">
+            <div className="space-y-3 p-5">
+              <h3 className="text-base font-semibold text-content-primary">
+                {t("archiveAllTitle")}
+              </h3>
+              <p className="text-sm text-content-muted">{t("archiveAllDesc")}</p>
+              <div className="space-y-0.5">
+                {(
+                  [
+                    ["month", t("archiveOptionMonth")],
+                    ["half", t("archiveOptionHalfMonth")],
+                    ["week", t("archiveOptionWeek")],
+                    ["custom", t("archiveOptionCustom")],
+                  ] as const
+                ).map(([mode, label]) => (
+                  <label
+                    key={mode}
+                    className="flex items-center gap-2 rounded-md px-2 py-1.5 text-sm text-content-primary hover:bg-input"
+                  >
+                    <input
+                      type="radio"
+                      name="archiveAllMode"
+                      className="h-4 w-4 accent-blue-600"
+                      checked={archiveAll.mode === mode}
+                      disabled={archiveAll.busy}
+                      onChange={() =>
+                        setArchiveAll((s) =>
+                          s ? { ...s, mode, result: null, error: null } : s
+                        )
+                      }
+                    />
+                    <span>{label}</span>
+                  </label>
+                ))}
+              </div>
+              {archiveAll.mode === "custom" && (
+                <input
+                  type="date"
+                  value={archiveAll.date}
+                  disabled={archiveAll.busy}
+                  onChange={(e) =>
+                    setArchiveAll((s) => (s ? { ...s, date: e.target.value } : s))
+                  }
+                  className="bg-input border border-border rounded px-2 py-1 text-sm focus:ring-2 focus:ring-blue-500 focus:outline-none"
+                />
+              )}
+              <div className="rounded-md border border-border bg-input px-3 py-2.5 text-sm text-content-muted">
+                {t("archiveAllConfirm", {
+                  date: new Date(cutoffFor(archiveAll)).toLocaleDateString(
+                    locale === "zh" ? "zh-CN" : "en-US"
+                  ),
+                })}
+              </div>
+              {archiveAll.error && (
+                <div className="rounded-md border border-red-500/40 bg-red-900/20 px-3 py-2 text-sm text-red-300">
+                  {t("archiveAllFailed")}: {archiveAll.error}
+                </div>
+              )}
+              {archiveAll.result && archiveAll.result.archived === 0 && (
+                <div className="rounded-md border border-border bg-input px-3 py-2 text-sm text-content-muted">
+                  {t("archiveAllEmpty")}
+                </div>
+              )}
+              {archiveAll.result && archiveAll.result.archived > 0 && (
+                <div className="rounded-md border border-emerald-500/40 bg-emerald-900/20 px-3 py-2 text-sm text-emerald-300">
+                  {t("archiveAllDone", {
+                    archived: archiveAll.result.archived,
+                    skipped: archiveAll.result.skipped,
+                  })}
+                </div>
+              )}
+              {archiveAll.result && archiveAll.result.errors.length > 0 && (
+                <div className="space-y-1 rounded-md border border-red-500/40 bg-red-900/20 px-3 py-2 text-xs text-red-300">
+                  {archiveAll.result.errors.slice(0, 3).map((err, i) => (
+                    <div key={i} className="break-all">
+                      {err}
+                    </div>
+                  ))}
+                </div>
+              )}
+            </div>
+            <div className="flex justify-end gap-2 border-t border-border bg-footer px-5 py-3">
+              <button
+                type="button"
+                disabled={archiveAll.busy}
+                onClick={() => setArchiveAll(null)}
+                className="px-3 py-1.5 text-sm rounded border border-border hover:bg-hover-2 disabled:opacity-50"
+              >
+                {archiveAll.result ? t("close") : t("cancel")}
+              </button>
+              <button
+                type="button"
+                disabled={archiveAll.busy}
+                onClick={runArchiveAll}
+                className="px-3 py-1.5 text-sm rounded bg-blue-600 text-white hover:bg-blue-500 disabled:opacity-50"
+              >
+                {archiveAll.busy ? t("archiveAllRunning") : t("sessionsArchiveAll")}
+              </button>
+            </div>
+          </div>
+        </div>
+      )}
+
       {/* Confirm dialog */}
       {confirm && (
         <div className="fixed inset-0 z-50 flex items-center justify-center bg-black/60 p-4">
diff --git a/src/hooks/useSessions.ts b/src/hooks/useSessions.ts
index d4c803c..338f4fe 100644
--- a/src/hooks/useSessions.ts
+++ b/src/hooks/useSessions.ts
@@ -2,6 +2,7 @@ import { useCallback, useEffect, useState } from "react";
 import { invoke } from "@tauri-apps/api/core";
 import type {
   ActionResponse,
+  BulkArchiveResult,
   PreviewResult,
   SessionStatusFilter,
   SessionsResult,
@@ -54,6 +55,17 @@ export function useSessions() {
     [refresh]
   );
 
+  const archiveBefore = useCallback(
+    async (cutoffMs: number) => {
+      const result = await invoke<BulkArchiveResult>("archive_sessions_before", {
+        cutoffMs,
+      });
+      await refresh();
+      return result;
+    },
+    [refresh]
+  );
+
   const deleteSession = useCallback(
     async (workspaceId: string, sessionId: string, sessionStatus?: string) => {
       await invoke<ActionResponse>("delete_session", {
@@ -100,6 +112,7 @@ export function useSessions() {
     refresh,
     archiveSession,
     unarchiveSession,
+    archiveBefore,
     deleteSession,
     deleteWorkspace,
     getPreview,
diff --git a/src/i18n/en.ts b/src/i18n/en.ts
index 42cadcb..30a8dd5 100644
--- a/src/i18n/en.ts
+++ b/src/i18n/en.ts
@@ -225,6 +225,19 @@ export const enTranslations: Record<TranslationKey, string> = {
   roleUser: "User",
   roleAssistant: "Assistant",
   roleSystem: "System",
+  sessionsArchiveAll: "Archive old sessions",
+  archiveAllTitle: "Archive old sessions",
+  archiveAllDesc:
+    "Archives every active session whose last activity is older than the selected date. Files are kept and usage stats stay intact.",
+  archiveOptionMonth: "Older than 1 month",
+  archiveOptionHalfMonth: "Older than 15 days",
+  archiveOptionWeek: "Older than 1 week",
+  archiveOptionCustom: "Specific date",
+  archiveAllConfirm: "Archive every active session last active before {date}. Continue?",
+  archiveAllRunning: "Archiving…",
+  archiveAllDone: "Archived {archived} sessions, skipped {skipped}",
+  archiveAllFailed: "Archive failed",
+  archiveAllEmpty: "No sessions match",
 
   // Heatmap
   noData: "No data",
diff --git a/src/i18n/zh.ts b/src/i18n/zh.ts
index 8c54db0..c751995 100644
--- a/src/i18n/zh.ts
+++ b/src/i18n/zh.ts
@@ -220,6 +220,18 @@ export const zhTranslations = {
   roleUser: "用户",
   roleAssistant: "助手",
   roleSystem: "系统",
+  sessionsArchiveAll: "一键归档",
+  archiveAllTitle: "一键归档会话",
+  archiveAllDesc: "将归档最后活跃时间早于所选日期的全部活跃会话；文件保留，统计不受影响。",
+  archiveOptionMonth: "1 个月前",
+  archiveOptionHalfMonth: "半个月前",
+  archiveOptionWeek: "1 星期前",
+  archiveOptionCustom: "指定日期",
+  archiveAllConfirm: "将归档最后活跃时间早于 {date} 的全部活跃会话。确认？",
+  archiveAllRunning: "正在归档…",
+  archiveAllDone: "已归档 {archived} 个会话，跳过 {skipped} 个",
+  archiveAllFailed: "归档失败",
+  archiveAllEmpty: "没有符合条件的会话",
 
   // Heatmap
   noData: "暂无数据",
diff --git a/src/lib/models-dev-full.json b/src/lib/models-dev-full.json
index 011efb3..1fefea9 100644
--- a/src/lib/models-dev-full.json
+++ b/src/lib/models-dev-full.json
@@ -1,5 +1,5 @@
 {
-  "last_updated": "2026-09-10",
+  "last_updated": "2026-09-13",
   "providers": {
     "subconscious": {
       "id": "subconscious",
@@ -359,6 +359,77 @@
       "id": "bothub",
       "name": "Bothub",
       "models": [
+        {
+          "id": "deepseek-v4-pro-0813",
+          "name": "DeepSeek V4 Pro 0813",
+          "cost": {
+            "input": 1.61,
+            "output": 4.84
+          },
+          "context": 1000000,
+          "output_limit": 384000,
+          "reasoning": true,
+          "tool_call": true,
+          "structured_output": true
+        },
+        {
+          "id": "deepseek-v4-flash-0731",
+          "name": "DeepSeek V4 Flash 0731",
+          "cost": {
+            "input": 0.1,
+            "output": 0.28
+          },
+          "context": 1000000,
+          "output_limit": 384000,
+          "reasoning": true,
+          "tool_call": true,
+          "structured_output": true
+        },
+        {
+          "id": "gpt-5.6-luna",
+          "name": "GPT-5.6 Luna",
+          "cost": {
+            "input": 0.06,
+            "output": 0.37
+          },
+          "context": 1050000,
+          "input_limit": 922000,
+          "output_limit": 128000,
+          "reasoning": true,
+          "tool_call": true,
+          "structured_output": true,
+          "image": true
+        },
+        {
+          "id": "glm-5.3-flash",
+          "name": "GLM-5.3-Flash",
+          "cost": {
+            "input": 0.12,
+            "output": 0.44
+          },
+          "context": 1000000,
+          "output_limit": 131072,
+          "reasoning": true,
+          "tool_call": true,
+          "structured_output": true,
+          "image": true,
+          "video": true
+        },
+        {
+          "id": "muse-spark-1.3-contributor",
+          "name": "Muse Spark 1.3 Contributor",
+          "cost": {
+            "input": 0.1,
+            "output": 0.2
+          },
+          "context": 1048576,
+          "output_limit": 943718,
+          "reasoning": true,
+          "tool_call": true,
+          "structured_output": true,
+          "image": true,
+          "video": true
+        },
         {
           "id": "nemotron-3-ultra-550b-a55b:free",
           "name": "Nemotron 3 Ultra (free)",
@@ -384,6 +455,19 @@
           "tool_call": true,
           "structured_output": true,
           "image": true
+        },
+        {
+          "id": "glm-5.3",
+          "name": "GLM-5.3",
+          "cost": {
+            "input": 1.72,
+            "output": 5.41
+          },
+          "context": 1000000,
+          "output_limit": 131072,
+          "reasoning": true,
+          "tool_call": true,
+          "structured_output": true
         }
       ]
     },
@@ -526,6 +610,21 @@
           "output_limit": 16384,
           "tool_call": true
         },
+        {
+          "id": "deepseek-v4.1-flash",
+          "name": "DeepSeek V4.1 Flash",
+          "cost": {
+            "input": 0.255552,
+            "output": 1.27776,
+            "cache_read": 0.0127776
+          },
+          "context": 1000000,
+          "output_limit": 384000,
+          "reasoning": true,
+          "tool_call": true,
+          "structured_output": true,
+          "image": true
+        },
         {
           "id": "glm-5.2-honey-lite",
           "name": "GLM-5.2 Honey Lite",
@@ -1856,6 +1955,15 @@
           "tool_call": true,
           "image": true
         },
+        {
+          "id": "deepseek-v4-flash",
+          "name": "DeepSeek V4 Flash",
+          "context": 1000000,
+          "output_limit": 384000,
+          "reasoning": true,
+          "tool_call": true,
+          "structured_output": true
+        },
         {
           "id": "claude-opus-4-8",
           "name": "Claude Opus 4.8",
@@ -1864,6 +1972,15 @@
           "reasoning": true,
           "tool_call": true,
           "image": true
+        },
+        {
+          "id": "glm-5.3",
+          "name": "GLM-5.3",
+          "context": 1000000,
+          "output_limit": 131072,
+          "reasoning": true,
+          "tool_call": true,
+          "structured_output": true
         }
       ]
     },
@@ -5549,6 +5666,18 @@
           "output_limit": 32768,
           "image": true
         },
+        {
+          "id": "mistralai/mistral-small-24b-instruct-2501",
+          "name": "Mistral Small 24B",
+          "cost": {
+            "input": 0.1155,
+            "output": 0.3465
+          },
+          "context": 32768,
+          "input_limit": 32768,
+          "output_limit": 8192,
+          "tool_call": true
+        },
         {
           "id": "mistralai/mixtral-8x22b-instruct-v0.1",
           "name": "Mixtral 8x22B",
@@ -7243,6 +7372,21 @@
           "tool_call": true,
           "image": true
         },
+        {
+          "id": "TEE/nemotron-3.5-lightning",
+          "name": "Nvidia Nemotron 3.5 Lightning TEE",
+          "cost": {
+            "input": 0.08,
+            "output": 0.2,
+            "cache_read": 0.04
+          },
+          "context": 262144,
+          "input_limit": 262144,
+          "output_limit": 65536,
+          "reasoning": true,
+          "tool_call": true,
+          "structured_output": true
+        },
         {
           "id": "TEE/glm-5.2",
           "name": "GLM 5.2 TEE",
@@ -7307,9 +7451,9 @@
           "id": "TEE/gpt-oss-20b",
           "name": "GPT-OSS 20B TEE",
           "cost": {
-            "input": 0.2,
-            "output": 0.8,
-            "cache_read": 0.1
+            "input": 0.04,
+            "output": 0.15,
+            "cache_read": 0.02
           },
           "context": 131072,
           "input_limit": 131072,
@@ -7711,9 +7855,9 @@
           "id": "sakana/fugu-ultra",
           "name": "Fugu Ultra",
           "cost": {
-            "input": 5.25,
-            "output": 31.5,
-            "cache_read": 0.525
+            "input": 5,
+            "output": 30,
+            "cache_read": 0.5
           },
           "context": 1000000,
           "input_limit": 1000000,
@@ -7723,13 +7867,29 @@
           "structured_output": true,
           "image": true
         },
+        {
+          "id": "sakana/fugu-max",
+          "name": "Fugu Max",
+          "cost": {
+            "input": 2,
+            "output": 6,
+            "cache_read": 0.25
+          },
+          "context": 1000000,
+          "input_limit": 1000000,
+          "output_limit": 128000,
+          "reasoning": true,
+          "tool_call": true,
+          "structured_output": true,
+          "image": true
+        },
         {
           "id": "sakana/fugu-ultra-v1.1",
           "name": "Fugu Ultra v1.1",
           "cost": {
-            "input": 5.25,
-            "output": 31.5,
-            "cache_read": 0.525
+            "input": 5,
+            "output": 30,
+            "cache_read": 0.5
           },
           "context": 1000000,
           "input_limit": 1000000,
@@ -8219,6 +8379,19 @@
           "input_limit": 1000000,
           "output_limit": 131072
         },
+        {
+          "id": "lightonai/LightOnOCR-2-1B",
+          "name": "LightOnOCR 2",
+          "cost": {
+            "input": 0.1785,
+            "output": 0.3465
+          },
+          "context": 32768,
+          "input_limit": 32768,
+          "output_limit": 8192,
+          "tool_call": true,
+          "image": true
+        },
         {
           "id": "anthracite-org/magnum-v4-72b",
           "name": "Magnum v4 72B",
@@ -8377,7 +8550,20 @@
           },
           "context": 131072,
           "input_limit": 131072,
-          "output_limit": 16384
+          "output_limit": 16384,
+          "tool_call": true
+        },
+        {
+          "id": "meta-llama/llama-3.1-405b-instruct",
+          "name": "Llama 3.1 405B",
+          "cost": {
+            "input": 2.0265,
+            "output": 2.0265
+          },
+          "context": 131072,
+          "input_limit": 131072,
+          "output_limit": 8192,
+          "tool_call": true
         },
         {
           "id": "meta-llama/llama-3.2-3b-instruct",
@@ -8718,6 +8904,23 @@
           "structured_output": true,
           "image": true
         },
+        {
+          "id": "openai/gpt-terra-latest",
+          "name": "GPT Terra Latest",
+          "cost": {
+            "input": 2,
+            "output": 12,
+            "cache_read": 0.2,
+            "cache_write": 2.5
+          },
+          "context": 1050000,
+          "input_limit": 1050000,
+          "output_limit": 128000,
+          "reasoning": true,
+          "tool_call": true,
+          "structured_output": true,
+          "image": true
+        },
         {
           "id": "openai/gpt-4.1-mini",
           "name": "GPT 4.1 Mini",
@@ -8984,6 +9187,40 @@
           "structured_output": true,
           "image": true
         },
+        {
+          "id": "openai/gpt-sol-latest",
+          "name": "GPT Sol Latest",
+          "cost": {
+            "input": 2,
+            "output": 10,
+            "cache_read": 0.2,
+            "cache_write": 2.5
+          },
+          "context": 1050000,
+          "input_limit": 1050000,
+          "output_limit": 128000,
+          "reasoning": true,
+          "tool_call": true,
+          "structured_output": true,
+          "image": true
+        },
+        {
+          "id": "openai/gpt-luna-latest",
+          "name": "GPT Luna Latest",
+          "cost": {
+            "input": 0.2,
+            "output": 1.2,
+            "cache_read": 0.02,
+            "cache_write": 0.25
+          },
+          "context": 1050000,
+          "input_limit": 1050000,
+          "output_limit": 128000,
+          "reasoning": true,
+          "tool_call": true,
+          "structured_output": true,
+          "image": true
+        },
         {
           "id": "openai/gpt-5.4-mini",
           "name": "GPT 5.4 Mini",
@@ -9011,6 +9248,23 @@
           "input_limit": 16385,
           "output_limit": 4096
         },
+        {
+          "id": "openai/gpt-astra-latest",
+          "name": "GPT Astra Latest",
+          "cost": {
+            "input": 10,
+            "output": 50,
+            "cache_read": 1,
+            "cache_write": 12.5
+          },
+          "context": 1050000,
+          "input_limit": 1050000,
+          "output_limit": 128000,
+          "reasoning": true,
+          "tool_call": true,
+          "structured_output": true,
+          "image": true
+        },
         {
           "id": "openai/gpt-5-mini",
           "name": "GPT 5 Mini",
@@ -11502,12 +11756,12 @@
           "id": "glm-5.3",
           "name": "GLM5.3",
           "cost": {
-            "input": 1.4,
-            "output": 4.4,
-            "cache_read": 0.26
+            "input": 0.95,
+            "output": 3.4,
+            "cache_read": 0.2
           },
           "context": 1048576,
-          "output_limit": 1048576,
+          "output_limit": 128000,
           "reasoning": true,
           "tool_call": true,
           "structured_output": true
@@ -13241,6 +13495,25 @@
           "reasoning": true,
           "tool_call": true
         },
+        {
+          "id": "deepseek-v4-pro:0813",
+          "name": "DeepSeek V4 Pro 0813",
+          "context": 1048576,
+          "output_limit": 1048576,
+          "reasoning": true,
+          "tool_call": true,
+          "structured_output": true
+        },
+        {
+          "id": "deepseek-v4.1-flash",
+          "name": "DeepSeek V4.1 Flash",
+          "context": 1048576,
+          "output_limit": 384000,
+          "reasoning": true,
+          "tool_call": true,
+          "structured_output": true,
+          "image": true
+        },
         {
           "id": "nemotron-3-nano:30b",
           "name": "nemotron-3-nano:30b",
@@ -15349,6 +15622,23 @@
           "structured_output": true,
           "image": true
         },
+        {
+          "id": "aws-mantle/gpt-6-astra",
+          "name": "GPT-6 Astra (AWS Mantle)",
+          "cost": {
+            "input": 10,
+            "output": 50,
+            "cache_read": 1,
+            "cache_write": 12.5
+          },
+          "context": 1050000,
+          "input_limit": 922000,
+          "output_limit": 128000,
+          "reasoning": true,
+          "tool_call": true,
+          "structured_output": true,
+          "image": true
+        },
         {
           "id": "aws-mantle/gpt-5.6-luna",
           "name": "GPT-5.6 Luna (AWS Mantle)",
@@ -16208,6 +16498,22 @@
           "image": true,
           "video": true
         },
+        {
+          "id": "alibaba/kimi-k3",
+          "name": "Kimi K3 (Alibaba Cloud)",
+          "cost": {
+            "input": 3,
+            "output": 15,
+            "cache_read": 0.3
+          },
+          "context": 1048576,
+          "output_limit": 1048576,
+          "reasoning": true,
+          "tool_call": true,
+          "structured_output": true,
+          "image": true,
+          "video": true
+        },
         {
           "id": "alibaba/qwen3.6-35b-a3b",
           "name": "Qwen3.6 35B A3B (Alibaba Cloud)",
@@ -16404,6 +16710,22 @@
           "output_limit": 32000,
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@@ -16563,6 +16885,21 @@
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@@ -17047,6 +17384,32 @@
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@@ -17097,6 +17460,21 @@
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@@ -17781,6 +18159,20 @@
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@@ -18149,6 +18541,36 @@
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@@ -18199,6 +18621,21 @@
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@@ -18465,7 +18902,7 @@
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@@ -18499,6 +18936,19 @@
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@@ -19470,6 +19920,242 @@
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           "name": "Grok 4 (xAI)",
@@ -19888,6 +20574,21 @@
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           "name": "Kimi K3 (Fireworks AI)",
@@ -21728,6 +22429,21 @@
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@@ -25434,6 +26150,17 @@
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@@ -28783,6 +29510,94 @@
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@@ -28973,19 +29788,6 @@
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@@ -29004,15 +29806,16 @@
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@@ -34049,6 +34852,33 @@
           "reasoning": true,
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           "name": "GPT-4.1 nano",
@@ -34080,6 +34910,21 @@
           "image": true,
           "video": true
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+        {
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@@ -34097,6 +34942,20 @@
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           "name": "Claude Opus 5",
@@ -34521,6 +35380,20 @@
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@@ -34569,6 +35442,20 @@
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@@ -35002,6 +35889,21 @@
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@@ -40533,6 +41487,20 @@
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@@ -47200,6 +48222,21 @@
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@@ -55916,6 +56957,19 @@
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@@ -56025,6 +57079,17 @@
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@@ -56562,6 +57627,21 @@
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@@ -56970,6 +58050,20 @@
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@@ -57104,6 +58198,21 @@
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@@ -57192,6 +58301,21 @@
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@@ -57521,6 +58645,20 @@
       "id": "inception",
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@@ -60213,6 +61351,21 @@
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@@ -60355,6 +61508,14 @@
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@@ -61716,6 +62877,18 @@
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@@ -62499,6 +63672,21 @@
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@@ -73612,7 +75112,7 @@
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@@ -74600,6 +76112,17 @@
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@@ -75024,6 +76558,17 @@
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@@ -93942,6 +96076,21 @@
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@@ -101968,6 +104157,16 @@
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@@ -102250,8 +104449,8 @@
           "id": "deepinfra/deepseek-ai/DeepSeek-V4.1-Flash",
           "name": "DeepSeek V4.1 Flash (Deep Infra)",
           "cost": {
-            "input": 0.3,
-            "output": 1.2,
+            "input": 0.2,
+            "output": 0.6,
             "cache_read": 0.006
           },
           "context": 1048576,
@@ -102327,6 +104526,45 @@
           "structured_output": true,
           "image": true
         },
+        {
+          "id": "deepinfra/google/gemma-3-4b-it",
+          "name": "Gemma 3 4B IT (Deep Infra)",
+          "cost": {
+            "input": 0.05,
+            "output": 0.1
+          },
+          "context": 131072,
+          "output_limit": 131072,
+          "tool_call": true,
+          "structured_output": true,
+          "image": true
+        },
+        {
+          "id": "deepinfra/google/gemma-3-27b-it",
+          "name": "Gemma 3 27B IT (Deep Infra)",
+          "cost": {
+            "input": 0.08,
+            "output": 0.16
+          },
+          "context": 131072,
+          "output_limit": 131072,
+          "tool_call": true,
+          "structured_output": true,
+          "image": true
+        },
+        {
+          "id": "deepinfra/google/gemma-3-12b-it",
+          "name": "Gemma 3 12B IT (Deep Infra)",
+          "cost": {
+            "input": 0.05,
+            "output": 0.15
+          },
+          "context": 131072,
+          "output_limit": 131072,
+          "tool_call": true,
+          "structured_output": true,
+          "image": true
+        },
         {
           "id": "deepinfra/zai-org/GLM-4.7-Flash",
           "name": "GLM-4.7-Flash (Deep Infra)",
@@ -102726,7 +104964,7 @@
             "output": 0.14
           },
           "context": 128000,
-          "output_limit": 8192,
+          "output_limit": 10000,
           "tool_call": true,
           "structured_output": true
         },
@@ -102749,7 +104987,7 @@
             "output": 0.24
           },
           "context": 300000,
-          "output_limit": 8192,
+          "output_limit": 10000,
           "tool_call": true,
           "structured_output": true,
           "image": true
@@ -102766,6 +105004,27 @@
           "reasoning": true,
           "tool_call": true
         },
+        {
+          "id": "amazon/google.gemma-3-12b-it@us",
+          "name": "Gemma 3 12B IT (Amazon Bedrock, US)",
+          "cost": {
+            "input": 0.09,
+            "output": 0.29
+          },
+          "context": 128000,
+          "output_limit": 131072,
+          "image": true
+        },
+        {
+          "id": "amazon/mistral.voxtral-mini-3b-2507",
+          "name": "Voxtral Mini 3B 2507 (Amazon Bedrock)",
+          "cost": {
+            "input": 0.04,
+            "output": 0.04
+          },
+          "context": 128000,
+          "output_limit": 32768
+        },
         {
           "id": "amazon/amazon.nova-pro-v1:0@us",
           "name": "Nova Pro (US)",
@@ -102774,11 +105033,33 @@
             "output": 3.2
           },
           "context": 300000,
-          "output_limit": 8192,
+          "output_limit": 10000,
           "tool_call": true,
           "structured_output": true,
           "image": true
         },
+        {
+          "id": "amazon/google.gemma-3-12b-it",
+          "name": "Gemma 3 12B IT (Amazon Bedrock)",
+          "cost": {
+            "input": 0.09,
+            "output": 0.29
+          },
+          "context": 128000,
+          "output_limit": 131072,
+          "image": true
+        },
+        {
+          "id": "amazon/openai.gpt-oss-safeguard-20b",
+          "name": "GPT OSS Safeguard 20B (Amazon Bedrock)",
+          "cost": {
+            "input": 0.07,
+            "output": 0.2
+          },
+          "context": 128000,
+          "output_limit": 131072,
+          "reasoning": true
+        },
         {
           "id": "amazon/amazon.nova-lite-v1:0",
           "name": "Nova Lite",
@@ -102787,7 +105068,7 @@
             "output": 0.24
           },
           "context": 300000,
-          "output_limit": 8192,
+          "output_limit": 10000,
           "tool_call": true,
           "structured_output": true,
           "image": true
@@ -102800,11 +105081,22 @@
             "output": 3.2
           },
           "context": 300000,
-          "output_limit": 8192,
+          "output_limit": 10000,
           "tool_call": true,
           "structured_output": true,
           "image": true
         },
+        {
+          "id": "amazon/openai.gpt-oss-safeguard-20b@us",
+          "name": "GPT OSS Safeguard 20B (Amazon Bedrock, US)",
+          "cost": {
+            "input": 0.07,
+            "output": 0.2
+          },
+          "context": 128000,
+          "output_limit": 131072,
+          "reasoning": true
+        },
         {
           "id": "amazon/moonshot.kimi-k2-thinking",
           "name": "Kimi K2 Thinking (Amazon Bedrock)",
@@ -102816,6 +105108,17 @@
           "output_limit": 262144,
           "reasoning": true
         },
+        {
+          "id": "amazon/google.gemma-3-27b-it",
+          "name": "Gemma 3 27B IT (Amazon Bedrock)",
+          "cost": {
+            "input": 0.23,
+            "output": 0.38
+          },
+          "context": 128000,
+          "output_limit": 131072,
+          "image": true
+        },
         {
           "id": "amazon/amazon.nova-micro-v1:0",
           "name": "Nova Micro",
@@ -102824,10 +105127,20 @@
             "output": 0.14
           },
           "context": 128000,
-          "output_limit": 8192,
+          "output_limit": 10000,
           "tool_call": true,
           "structured_output": true
         },
+        {
+          "id": "amazon/mistral.voxtral-mini-3b-2507@us",
+          "name": "Voxtral Mini 3B 2507 (Amazon Bedrock, US)",
+          "cost": {
+            "input": 0.04,
+            "output": 0.04
+          },
+          "context": 128000,
+          "output_limit": 32768
+        },
         {
           "id": "amazon/mistral.pixtral-large-2502-v1:0@us",
           "name": "Pixtral Large (25.02) (Amazon Bedrock, US)",
@@ -102839,6 +105152,17 @@
           "output_limit": 8192,
           "tool_call": true
         },
+        {
+          "id": "amazon/google.gemma-3-27b-it@us",
+          "name": "Gemma 3 27B IT (Amazon Bedrock, US)",
+          "cost": {
+            "input": 0.23,
+            "output": 0.38
+          },
+          "context": 128000,
+          "output_limit": 131072,
+          "image": true
+        },
         {
           "id": "amazon/zai.glm-4.7-flash",
           "name": "GLM-4.7-Flash (Amazon Bedrock)",
@@ -102851,6 +105175,48 @@
           "reasoning": true,
           "tool_call": true
         },
+        {
+          "id": "amazon/google.gemma-3-4b-it",
+          "name": "Gemma 3 4B IT (Amazon Bedrock)",
+          "cost": {
+            "input": 0.04,
+            "output": 0.08
+          },
+          "context": 128000,
+          "output_limit": 131072,
+          "image": true
+        },
+        {
+          "id": "amazon/mistral.voxtral-small-24b-2507",
+          "name": "Voxtral Small 24B 2507 (Amazon Bedrock)",
+          "cost": {
+            "input": 0.1,
+            "output": 0.3
+          },
+          "context": 128000,
+          "output_limit": 32768
+        },
+        {
+          "id": "amazon/mistral.voxtral-small-24b-2507@us",
+          "name": "Voxtral Small 24B 2507 (Amazon Bedrock, US)",
+          "cost": {
+            "input": 0.1,
+            "output": 0.3
+          },
+          "context": 128000,
+          "output_limit": 32768
+        },
+        {
+          "id": "amazon/google.gemma-3-4b-it@us",
+          "name": "Gemma 3 4B IT (Amazon Bedrock, US)",
+          "cost": {
+            "input": 0.04,
+            "output": 0.08
+          },
+          "context": 128000,
+          "output_limit": 131072,
+          "image": true
+        },
         {
           "id": "openai/gpt-5-nano",
           "name": "GPT-5 Nano",
@@ -103160,8 +105526,7 @@
           "name": "GPT-5.5 Pro",
           "cost": {
             "input": 30,
-            "output": 180,
-            "cache_read": 3
+            "output": 180
           },
           "context": 1050000,
           "input_limit": 922000,
@@ -103220,8 +105585,7 @@
           "name": "GPT-5.4 Pro",
           "cost": {
             "input": 30,
-            "output": 180,
-            "cache_read": 3
+            "output": 180
           },
           "context": 1050000,
           "input_limit": 922000,
@@ -103342,8 +105706,7 @@
           "name": "GPT Pro Latest (GPT-5.5 Pro)",
           "cost": {
             "input": 30,
-            "output": 180,
-            "cache_read": 3
+            "output": 180
           },
           "context": 1050000,
           "input_limit": 922000,
@@ -103721,6 +106084,21 @@
           "tool_call": true,
           "structured_output": true
         },
+        {
+          "id": "together_ai/deepseek-ai/DeepSeek-V4.1-Flash",
+          "name": "DeepSeek V4.1 Flash (Together AI)",
+          "cost": {
+            "input": 0.3,
+            "output": 1.2,
+            "cache_read": 0.006
+          },
+          "context": 1048576,
+          "output_limit": 384000,
+          "reasoning": true,
+          "tool_call": true,
+          "structured_output": true,
+          "image": true
+        },
         {
           "id": "together_ai/deepseek-ai/DeepSeek-V4-Pro-0813",
           "name": "DeepSeek V4 Pro 0813 (Together AI)",
@@ -104419,8 +106797,8 @@
           "id": "ionos/meta-llama/Llama-3.3-70B-Instruct",
           "name": "Llama-3.3-70B-Instruct (IONOS)",
           "cost": {
-            "input": 0.75504,
-            "output": 0.75504
+            "input": 0.75348,
+            "output": 0.75348
           },
           "context": 128000,
           "output_limit": 4096
@@ -104429,8 +106807,8 @@
           "id": "ionos/openai/gpt-oss-120b",
           "name": "GPT OSS 120B (IONOS)",
           "cost": {
-            "input": 0.17424,
-            "output": 0.75504
+            "input": 0.17388,
+            "output": 0.75348
           },
           "context": 131072,
           "output_limit": 32768,
diff --git a/src/lib/models-dev.json b/src/lib/models-dev.json
index d3f673a..47182aa 100644
--- a/src/lib/models-dev.json
+++ b/src/lib/models-dev.json
@@ -1,5 +1,5 @@
 {
-  "last_updated": "2026-09-10",
+  "last_updated": "2026-09-13",
   "subconscious/subconscious/glm-5.2": {
     "name": "GLM-5.2",
     "context": 1000000,
@@ -287,6 +287,66 @@
       "output": 3.072
     }
   },
+  "bothub/deepseek-v4-pro-0813": {
+    "name": "DeepSeek V4 Pro 0813",
+    "context": 1000000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "cost": {
+      "input": 1.61,
+      "output": 4.84
+    }
+  },
+  "bothub/deepseek-v4-flash-0731": {
+    "name": "DeepSeek V4 Flash 0731",
+    "context": 1000000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "cost": {
+      "input": 0.1,
+      "output": 0.28
+    }
+  },
+  "bothub/gpt-5.6-luna": {
+    "name": "GPT-5.6 Luna",
+    "context": 1050000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
+      "input": 0.06,
+      "output": 0.37
+    }
+  },
+  "bothub/glm-5.3-flash": {
+    "name": "GLM-5.3-Flash",
+    "context": 1000000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "video": true,
+    "cost": {
+      "input": 0.12,
+      "output": 0.44
+    }
+  },
+  "bothub/muse-spark-1.3-contributor": {
+    "name": "Muse Spark 1.3 Contributor",
+    "context": 1048576,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "video": true,
+    "cost": {
+      "input": 0.1,
+      "output": 0.2
+    }
+  },
   "bothub/nemotron-3-ultra-550b-a55b:free": {
     "name": "Nemotron 3 Ultra (free)",
     "context": 1000000,
@@ -309,6 +369,17 @@
       "output": 0
     }
   },
+  "bothub/glm-5.3": {
+    "name": "GLM-5.3",
+    "context": 1000000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "cost": {
+      "input": 1.72,
+      "output": 5.41
+    }
+  },
   "greenpt/deepseek-v4-flash-0731": {
     "name": "DeepSeek V4 Flash 0731",
     "context": 1000000,
@@ -424,6 +495,19 @@
       "output": 2.736
     }
   },
+  "greenpt/deepseek-v4.1-flash": {
+    "name": "DeepSeek V4.1 Flash",
+    "context": 1000000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
+      "input": 0.255552,
+      "output": 1.27776,
+      "cache_read": 0.0127776
+    }
+  },
   "greenpt/glm-5.2-honey-lite": {
     "name": "GLM-5.2 Honey Lite",
     "context": 1000000,
@@ -1471,6 +1555,13 @@
     "tool_call": true,
     "image": true
   },
+  "agentrouter/deepseek-v4-flash": {
+    "name": "DeepSeek V4 Flash",
+    "context": 1000000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true
+  },
   "agentrouter/claude-opus-4-8": {
     "name": "Claude Opus 4.8",
     "context": 1000000,
@@ -1478,6 +1569,13 @@
     "tool_call": true,
     "image": true
   },
+  "agentrouter/glm-5.3": {
+    "name": "GLM-5.3",
+    "context": 1000000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true
+  },
   "xiaomi-token-plan-cn/mimo-v2.5-tts": {
     "name": "MiMo-V2.5-TTS",
     "context": 8192,
@@ -4368,6 +4466,15 @@
       "cache_read": 0.2
     }
   },
+  "nano-gpt/mistralai/mistral-small-24b-instruct-2501": {
+    "name": "Mistral Small 24B",
+    "context": 32768,
+    "tool_call": true,
+    "cost": {
+      "input": 0.1155,
+      "output": 0.3465
+    }
+  },
   "nano-gpt/mistralai/mixtral-8x22b-instruct-v0.1": {
     "name": "Mixtral 8x22B",
     "context": 65536,
@@ -5726,6 +5833,18 @@
       "cache_read": 0.375
     }
   },
+  "nano-gpt/TEE/nemotron-3.5-lightning": {
+    "name": "Nvidia Nemotron 3.5 Lightning TEE",
+    "context": 262144,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "cost": {
+      "input": 0.08,
+      "output": 0.2,
+      "cache_read": 0.04
+    }
+  },
   "nano-gpt/TEE/glm-5.2": {
     "name": "GLM 5.2 TEE",
     "context": 1048576,
@@ -5778,9 +5897,9 @@
     "name": "GPT-OSS 20B TEE",
     "context": 131072,
     "cost": {
-      "input": 0.2,
-      "output": 0.8,
-      "cache_read": 0.1
+      "input": 0.04,
+      "output": 0.15,
+      "cache_read": 0.02
     }
   },
   "nano-gpt/TEE/qwen2.5-vl-72b-instruct": {
@@ -6096,9 +6215,22 @@
     "structured_output": true,
     "image": true,
     "cost": {
-      "input": 5.25,
-      "output": 31.5,
-      "cache_read": 0.525
+      "input": 5,
+      "output": 30,
+      "cache_read": 0.5
+    }
+  },
+  "nano-gpt/sakana/fugu-max": {
+    "name": "Fugu Max",
+    "context": 1000000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
+      "input": 2,
+      "output": 6,
+      "cache_read": 0.25
     }
   },
   "nano-gpt/sakana/fugu-ultra-v1.1": {
@@ -6109,9 +6241,9 @@
     "structured_output": true,
     "image": true,
     "cost": {
-      "input": 5.25,
-      "output": 31.5,
-      "cache_read": 0.525
+      "input": 5,
+      "output": 30,
+      "cache_read": 0.5
     }
   },
   "nano-gpt/Envoid/Llama-3.05-Nemotron-Tenyxchat-Storybreaker-70B": {
@@ -6489,6 +6621,16 @@
       "cache_read": 0.3026
     }
   },
+  "nano-gpt/lightonai/LightOnOCR-2-1B": {
+    "name": "LightOnOCR 2",
+    "context": 32768,
+    "tool_call": true,
+    "image": true,
+    "cost": {
+      "input": 0.1785,
+      "output": 0.3465
+    }
+  },
   "nano-gpt/anthracite-org/magnum-v4-72b": {
     "name": "Magnum v4 72B",
     "context": 16384,
@@ -6610,12 +6752,22 @@
   "nano-gpt/meta-llama/llama-3.1-8b-instruct": {
     "name": "Llama 3.1 8b Instruct",
     "context": 131072,
+    "tool_call": true,
     "cost": {
       "input": 0.0544,
       "output": 0.085,
       "cache_read": 0.0272
     }
   },
+  "nano-gpt/meta-llama/llama-3.1-405b-instruct": {
+    "name": "Llama 3.1 405B",
+    "context": 131072,
+    "tool_call": true,
+    "cost": {
+      "input": 2.0265,
+      "output": 2.0265
+    }
+  },
   "nano-gpt/meta-llama/llama-3.2-3b-instruct": {
     "name": "Llama 3.2 3b Instruct",
     "context": 131072,
@@ -6886,6 +7038,20 @@
       "cache_write": 0.25
     }
   },
+  "nano-gpt/openai/gpt-terra-latest": {
+    "name": "GPT Terra Latest",
+    "context": 1050000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
+      "input": 2,
+      "output": 12,
+      "cache_read": 0.2,
+      "cache_write": 2.5
+    }
+  },
   "nano-gpt/openai/gpt-4.1-mini": {
     "name": "GPT 4.1 Mini",
     "context": 1047576,
@@ -7098,6 +7264,34 @@
       "cache_write": 2.5
     }
   },
+  "nano-gpt/openai/gpt-sol-latest": {
+    "name": "GPT Sol Latest",
+    "context": 1050000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
+      "input": 2,
+      "output": 10,
+      "cache_read": 0.2,
+      "cache_write": 2.5
+    }
+  },
+  "nano-gpt/openai/gpt-luna-latest": {
+    "name": "GPT Luna Latest",
+    "context": 1050000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
+      "input": 0.2,
+      "output": 1.2,
+      "cache_read": 0.02,
+      "cache_write": 0.25
+    }
+  },
   "nano-gpt/openai/gpt-5.4-mini": {
     "name": "GPT 5.4 Mini",
     "context": 400000,
@@ -7119,6 +7313,20 @@
       "output": 1.5
     }
   },
+  "nano-gpt/openai/gpt-astra-latest": {
+    "name": "GPT Astra Latest",
+    "context": 1050000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
+      "input": 10,
+      "output": 50,
+      "cache_read": 1,
+      "cache_write": 12.5
+    }
+  },
   "nano-gpt/openai/gpt-5-mini": {
     "name": "GPT 5 Mini",
     "context": 400000,
@@ -9144,9 +9352,9 @@
     "tool_call": true,
     "structured_output": true,
     "cost": {
-      "input": 1.4,
-      "output": 4.4,
-      "cache_read": 0.26
+      "input": 0.95,
+      "output": 3.4,
+      "cache_read": 0.2
     }
   },
   "digitalocean/anthropic-claude-opus-5": {
@@ -10576,6 +10784,21 @@
     "reasoning": true,
     "tool_call": true
   },
+  "ollama-cloud/deepseek-v4-pro:0813": {
+    "name": "DeepSeek V4 Pro 0813",
+    "context": 1048576,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true
+  },
+  "ollama-cloud/deepseek-v4.1-flash": {
+    "name": "DeepSeek V4.1 Flash",
+    "context": 1048576,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true
+  },
   "ollama-cloud/nemotron-3-nano:30b": {
     "name": "nemotron-3-nano:30b",
     "context": 1048576,
@@ -12309,6 +12532,20 @@
       "cache_write": 6.875
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     "context": 278528,
@@ -13043,6 +13280,20 @@
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@@ -13211,6 +13462,20 @@
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+  "llmgateway-providers/runpod/kimi-k3": {
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+    "reasoning": true,
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@@ -13348,6 +13613,19 @@
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@@ -13768,6 +14046,28 @@
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@@ -13810,6 +14110,19 @@
       "output": 0.2
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+  "llmgateway-providers/together-ai/deepseek-v4.1-flash": {
+    "name": "DeepSeek V4.1 Flash (Together AI)",
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     "name": "Kimi K3 (Together AI)",
     "context": 1000000,
@@ -14396,6 +14709,18 @@
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+  "llmgateway-providers/novita/deepseek-v4.1-flash": {
+    "name": "DeepSeek V4.1 Flash (NovitaAI)",
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     "name": "Hy3 (NovitaAI)",
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@@ -14705,6 +15030,32 @@
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+  "llmgateway-providers/sakana/fugu-max": {
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+    "reasoning": true,
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@@ -14747,6 +15098,19 @@
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+  "llmgateway-providers/deepinfra/deepseek-v4.1-flash": {
+    "name": "DeepSeek V4.1 Flash (DeepInfra)",
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     "name": "Hy3 (DeepInfra)",
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@@ -14968,7 +15332,7 @@
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   "llmgateway-providers/consensusprotocol/deepseek-v4-flash": {
     "name": "DeepSeek V4 Flash (Consensus Protocol)",
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+    "context": 1050000,
     "reasoning": true,
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@@ -15002,6 +15366,17 @@
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+  "llmgateway-providers/consensusprotocol/gemma-4-31b-it": {
+    "name": "Gemma 4 31B IT (Consensus Protocol)",
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     "name": "GPT-5 Nano (Azure)",
     "context": 400000,
@@ -15803,6 +16178,208 @@
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+    "name": "Kimi K2.7 Code Highspeed (Tencent Cloud)",
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+    "reasoning": true,
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+  "llmgateway-providers/tencent/glm-5v-turbo": {
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+    "context": 200000,
+    "reasoning": true,
+    "tool_call": true,
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+    "reasoning": true,
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   "llmgateway-providers/xai/grok-4": {
     "name": "Grok 4 (xAI)",
     "context": 256000,
@@ -16161,6 +16738,19 @@
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+  "llmgateway-providers/fireworks/deepseek-v4.1-flash": {
+    "name": "DeepSeek V4.1 Flash (Fireworks AI)",
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   "llmgateway-providers/fireworks/kimi-k3": {
     "name": "Kimi K3 (Fireworks AI)",
     "context": 1040384,
@@ -17693,6 +18283,19 @@
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+  "aihubmix/deepseek-v4.1-flash": {
+    "name": "DeepSeek V4.1 Flash",
+    "context": 1000000,
+    "reasoning": true,
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   "aihubmix/gpt-5.1": {
     "name": "GPT-5.1",
     "context": 400000,
@@ -20803,6 +21406,15 @@
       "output": 1.22
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   },
+  "sap-ai-core/gemini-3.5-flash-lite": {
+    "name": "Gemini 3.5 Flash Lite",
+    "context": 1048576,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "video": true
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   "sap-ai-core/gpt-4.1": {
     "name": "gpt-4.1",
     "context": 1047576,
@@ -23585,6 +24197,82 @@
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+  "google-vertex/xai/grok-4.20-reasoning": {
+    "name": "Grok 4.20 (Reasoning)",
+    "context": 2000000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
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+    "name": "Grok 4.3",
+    "context": 200000,
+    "reasoning": true,
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+    "name": "Grok 4.20 (Non-Reasoning)",
+    "context": 2000000,
+    "tool_call": true,
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+    "context": 128000,
+    "reasoning": true,
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+    "reasoning": true,
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   "stepfun-ai/step-1-32k": {
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@@ -23724,17 +24412,6 @@
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     "context": 1000000,
@@ -23753,10 +24430,11 @@
     "reasoning": true,
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   "above/glm-5.2-fast": {
@@ -27931,6 +28609,29 @@
       "cache_write": 1.5625
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   },
+  "pioneer/mistral-medium": {
+    "name": "Mistral Medium 3",
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+    "tool_call": true,
+    "image": true,
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+  "pioneer/ministral-3b": {
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   "pioneer/gpt-4.1-nano": {
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@@ -27958,6 +28659,19 @@
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+  "pioneer/claude-opus-5-fast": {
+    "name": "Claude Opus 5",
+    "context": 1000000,
+    "reasoning": true,
+    "tool_call": true,
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   "pioneer/gpt-5.6-sol": {
     "name": "GPT-5.6 Sol",
     "context": 1050000,
@@ -27972,6 +28686,18 @@
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+  "pioneer/devstral-small-2": {
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+    "image": true,
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   "pioneer/claude-opus-5": {
     "name": "Claude Opus 5",
     "context": 1000000,
@@ -28338,6 +29064,18 @@
       "cache_write": 18.75
     }
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+  "pioneer/ministral-14b": {
+    "name": "Ministral 14B",
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+    "tool_call": true,
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   "pioneer/qwen3.7-plus": {
     "name": "Qwen3.7 Plus",
     "context": 1000000,
@@ -28379,6 +29117,18 @@
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+  "pioneer/magistral-medium": {
+    "name": "Magistral Medium (latest)",
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+    "reasoning": true,
+    "tool_call": true,
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@@ -28751,6 +29501,19 @@
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+    "reasoning": true,
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     "name": "GLM-5.2",
     "context": 1040000,
@@ -28775,6 +29538,19 @@
       "cache_write": 0.03
     }
   },
+  "pioneer/thinkingmachines/inkling-small": {
+    "name": "Inkling Small",
+    "context": 1000000,
+    "reasoning": true,
+    "tool_call": true,
+    "image": true,
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+      "cache_write": 0.5
+    }
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   "pioneer/fastino/gliguard-LLMGuardrails-300M": {
     "name": "GLiGuard LLM Guardrails 300M",
     "context": 8192,
@@ -29143,6 +29919,21 @@
       "cache_write": 0.95
     }
   },
+  "pioneer/moonshotai/Kimi-K3-Fast": {
+    "name": "Kimi K3",
+    "context": 1000000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "video": true,
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+      "cache_write": 4.5
+    }
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   "pioneer/moonshotai/Kimi-K3": {
     "name": "Kimi K3",
     "context": 1000000,
@@ -30554,9 +31345,9 @@
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-      "cache_write": 0.053
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   "hyper/deepseek-v4-pro-0813": {
@@ -30590,7 +31381,7 @@
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-      "cache_write": 0.05875
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@@ -30625,9 +31416,9 @@
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-      "cache_write": 0.229
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@@ -30648,9 +31439,9 @@
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-      "cache_write": 0.137
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   "hyper/glm-5.2": {
@@ -30710,7 +31501,20 @@
     "cost": {
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       "output": 2.5,
-      "cache_write": 0.3
+      "cache_read": 0.3
+    }
+  },
+  "hyper/deepseek-v4.1-flash": {
+    "name": "DeepSeek V4.1 Flash",
+    "context": 1048576,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
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@@ -30810,8 +31614,8 @@
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-      "output": 2.784,
-      "cache_write": 0.43
+      "output": 2.752,
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   "hyper/qwen3.8-max": {
@@ -30835,7 +31639,7 @@
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@@ -30845,9 +31649,9 @@
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-      "cache_write": 0.693
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@@ -30881,9 +31685,9 @@
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-      "cache_write": 0.09
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@@ -30892,6 +31696,7 @@
     "reasoning": true,
     "tool_call": true,
     "structured_output": true,
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       "output": 4.79072,
@@ -30905,7 +31710,7 @@
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@@ -30927,7 +31732,7 @@
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   "requesty/claude-sonnet-4-6": {
@@ -31411,6 +32216,19 @@
       "cache_read": 0.16
     }
   },
+  "requesty/deepseek-v4.1-flash@eu": {
+    "name": "DeepSeek V4.1 Flash (EU)",
+    "context": 1048576,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
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+    }
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   "requesty/gpt-5.4@eu": {
     "name": "GPT-5.4 (EU)",
     "context": 1050000,
@@ -31661,6 +32479,19 @@
       "cache_read": 0.0275
     }
   },
+  "requesty/deepseek-v4.1-flash": {
+    "name": "DeepSeek V4.1 Flash",
+    "context": 1048576,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
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+    }
+  },
   "requesty/hy3": {
     "name": "Hy3",
     "context": 262144,
@@ -31747,17 +32578,6 @@
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@@ -31922,9 +32742,9 @@
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-      "output": 33,
-      "cache_read": 0.55
+      "input": 4.4,
+      "output": 22,
+      "cache_read": 0.44
     }
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   "requesty/glm-5.2-fast": {
@@ -32121,17 +32941,6 @@
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   "requesty/seed-2.0-mini": {
     "name": "Seed 2.0 Mini",
     "context": 256000,
@@ -33400,6 +34209,18 @@
       "output": 5
     }
   },
+  "huggingface/deepseek-ai/DeepSeek-V4.1-Flash": {
+    "name": "DeepSeek V4.1 Flash",
+    "context": 1048576,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
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+      "output": 1.2
+    }
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   "huggingface/deepseek-ai/DeepSeek-V4-Pro-0813": {
     "name": "DeepSeek V4 Pro 0813",
     "context": 1000000,
@@ -33444,6 +34265,17 @@
       "cache_read": 0.003625
     }
   },
+  "huggingface/google/gemma-3-4b-it": {
+    "name": "Gemma 3 4B IT",
+    "context": 131072,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
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+      "output": 0.1
+    }
+  },
   "huggingface/google/gemma-4-31B-it": {
     "name": "Gemma 4 31B IT",
     "context": 262144,
@@ -33456,6 +34288,17 @@
       "output": 0.4
     }
   },
+  "huggingface/google/gemma-3-27b-it": {
+    "name": "Gemma 3 27B IT",
+    "context": 131072,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
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+    }
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   "huggingface/google/gemma-4-26B-A4B-it": {
     "name": "Gemma 4 26B A4B IT",
     "context": 262144,
@@ -33468,6 +34311,17 @@
       "output": 0.4
     }
   },
+  "huggingface/google/gemma-3-12b-it": {
+    "name": "Gemma 3 12B IT",
+    "context": 131072,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
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   "huggingface/zai-org/GLM-4.6V-Flash": {
     "name": "GLM-4.6V-Flash",
     "context": 131072,
@@ -36962,6 +37816,19 @@
       "output": 0
     }
   },
+  "nvidia/z-ai/glm-5.3-flash": {
+    "name": "GLM-5.3-Flash",
+    "context": 1000000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "video": true,
+    "cost": {
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+      "output": 0
+    }
+  },
   "nvidia/black-forest-labs/flux_1-kontext-dev": {
     "name": "FLUX.1-Kontext-dev",
     "context": 40960,
@@ -38972,6 +39839,19 @@
       "output": 1.5
     }
   },
+  "baseten/deepseek-ai/DeepSeek-V4.1-Flash": {
+    "name": "DeepSeek V4.1 Flash",
+    "context": 1048576,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
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+      "output": 1.2,
+      "cache_read": 0.03
+    }
+  },
   "baseten/deepseek-ai/DeepSeek-V4-Pro-0813": {
     "name": "DeepSeek V4 Pro 0813",
     "context": 1048576,
@@ -39050,6 +39930,7 @@
     "reasoning": true,
     "tool_call": true,
     "structured_output": true,
+    "image": true,
     "cost": {
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       "output": 4.4,
@@ -41026,18 +41907,6 @@
       "output": 1.85
     }
   },
-  "vercel/deepseek/deepseek-v4.1-flash-beta": {
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-  },
   "vercel/deepseek/deepseek-v4-flash": {
     "name": "DeepSeek V4 Flash",
     "context": 1000000,
@@ -41050,14 +41919,26 @@
       "cache_read": 0.028
     }
   },
+  "vercel/deepseek/deepseek-v4.1-flash": {
+    "name": "DeepSeek V4.1 Flash",
+    "context": 1048576,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
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+    }
+  },
   "vercel/deepseek/deepseek-v3.2": {
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     "structured_output": true,
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-      "output": 0.42,
-      "cache_read": 0.028
+      "input": 0.62,
+      "output": 1.85
     }
   },
   "vercel/deepseek/deepseek-v3.1-terminus": {
@@ -41098,7 +41979,6 @@
     "name": "DeepSeek-R1",
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     "reasoning": true,
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       "output": 5.4
@@ -41128,7 +42008,8 @@
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-      "cache_read": 0.2
+      "cache_read": 0.2,
+      "cache_write": 0.8
     }
   },
   "vercel/amazon/nova-lite": {
@@ -41140,7 +42021,8 @@
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-      "cache_read": 0.015
+      "cache_read": 0.015,
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   },
   "vercel/amazon/nova-micro": {
@@ -41150,7 +42032,8 @@
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-      "cache_read": 0.00875
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   },
   "vercel/inclusionai/ling-3.0-flash": {
@@ -43614,6 +44497,7 @@
     "context": 256000,
     "tool_call": true,
     "structured_output": true,
+    "image": true,
     "cost": {
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       "output": 0.25
@@ -46188,9 +47072,9 @@
     "reasoning": true,
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-      "cache_read": 0.035
+      "input": 0.132,
+      "output": 0.528,
+      "cache_read": 0.033
     }
   },
   "llmgateway/qwen3-coder-next": {
@@ -46250,6 +47134,17 @@
       "cache_read": 0.125
     }
   },
+  "llmgateway/hy4-preview": {
+    "name": "Hy4 preview",
+    "context": 1000000,
+    "reasoning": true,
+    "tool_call": true,
+    "cost": {
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+      "output": 2.501,
+      "cache_read": 0.042
+    }
+  },
   "llmgateway/ernie-4.5-vl-424b-a47b": {
     "name": "ERNIE 4.5 VL 424B A47B",
     "context": 123000,
@@ -46343,6 +47238,15 @@
       "cache_read": 1.25
     }
   },
+  "llmgateway/hy-mt2-plus": {
+    "name": "Hy-MT2 Plus",
+    "context": 8192,
+    "tool_call": true,
+    "cost": {
+      "input": 0.074,
+      "output": 0.295
+    }
+  },
   "llmgateway/gpt-5.6-luna": {
     "name": "GPT-5.6 Luna",
     "context": 1050000,
@@ -46802,6 +47706,19 @@
       "cache_write": 0.2
     }
   },
+  "llmgateway/fugu-max": {
+    "name": "Fugu Max",
+    "context": 1000000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
+      "input": 2,
+      "output": 6,
+      "cache_read": 0.25
+    }
+  },
   "llmgateway/gpt-5.4-mini": {
     "name": "GPT-5.4 mini",
     "context": 400000,
@@ -46859,9 +47776,9 @@
     "structured_output": true,
     "image": true,
     "cost": {
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-      "output": 0.297,
-      "cache_read": 0.012
+      "input": 0.1,
+      "output": 0.25,
+      "cache_read": 0.01
     }
   },
   "llmgateway/claude-haiku-4-5": {
@@ -47151,6 +48068,18 @@
       "output": 0.15
     }
   },
+  "llmgateway/glm-5-turbo": {
+    "name": "GLM-5-Turbo",
+    "context": 200000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "cost": {
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+      "output": 4,
+      "cache_read": 0.24
+    }
+  },
   "llmgateway/gpt-5-mini": {
     "name": "GPT-5 Mini",
     "context": 400000,
@@ -47264,6 +48193,19 @@
       "cache_read": 0.2
     }
   },
+  "llmgateway/glm-5v-turbo": {
+    "name": "GLM-5V-Turbo",
+    "context": 200000,
+    "reasoning": true,
+    "tool_call": true,
+    "image": true,
+    "video": true,
+    "cost": {
+      "input": 1.2,
+      "output": 4,
+      "cache_read": 0.24
+    }
+  },
   "llmgateway/gpt-4": {
     "name": "GPT-4",
     "context": 8192,
@@ -47338,6 +48280,19 @@
       "cache_read": 0.03
     }
   },
+  "llmgateway/fugu-ultra-v2.0": {
+    "name": "Fugu Ultra v2.0",
+    "context": 1000000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
+      "input": 5,
+      "output": 30,
+      "cache_read": 0.5
+    }
+  },
   "llmgateway/claude-sonnet-5": {
     "name": "Claude Sonnet 5",
     "context": 1000000,
@@ -47598,6 +48553,18 @@
       "output": 3.72
     }
   },
+  "inception/mercury-2.5": {
+    "name": "Mercury 2.5",
+    "context": 260000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "cost": {
+      "input": 0.04,
+      "output": 0.15,
+      "cache_read": 0.004
+    }
+  },
   "inception/mercury-edit-2": {
     "name": "Mercury Edit 2",
     "context": 128000,
@@ -49830,6 +50797,19 @@
       "cache_read": 0.06
     }
   },
+  "fireworks-ai/accounts/fireworks/models/deepseek-v4p1-flash": {
+    "name": "DeepSeek V4.1 Flash",
+    "context": 1000000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
+      "input": 0.22,
+      "output": 0.66,
+      "cache_read": 0.007
+    }
+  },
   "fireworks-ai/accounts/fireworks/models/kimi-k2p6": {
     "name": "Kimi K2.6",
     "context": 262000,
@@ -49952,6 +50932,12 @@
       "cache_read": 0.015
     }
   },
+  "fireworks-ai/accounts/fireworks/models/mistral-large-3-fp8": {
+    "name": "Mistral Large 3 675B Instruct 2512",
+    "context": 262144,
+    "tool_call": true,
+    "image": true
+  },
   "fireworks-ai/accounts/fireworks/models/glm-5p2": {
     "name": "GLM 5.2",
     "context": 1048575,
@@ -51087,6 +52073,16 @@
       "cache_read": 0.03
     }
   },
+  "empiriolabs/gemma-3-27b": {
+    "name": "Gemma 3 27B",
+    "context": 128000,
+    "structured_output": true,
+    "image": true,
+    "cost": {
+      "input": 0,
+      "output": 0
+    }
+  },
   "empiriolabs/qwen3-8-max-0902": {
     "name": "Qwen3.8 Max 0902",
     "context": 1000000,
@@ -51765,6 +52761,19 @@
       "cache_read": 1.31
     }
   },
+  "empiriolabs/fugu-ultra-v2-0": {
+    "name": "Fugu Ultra v2.0",
+    "context": 1000000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
+      "input": 5,
+      "output": 30,
+      "cache_read": 0.5
+    }
+  },
   "klokintegration/Kloker-Integration-Developer": {
     "name": "Kloker Integration Developer",
     "context": 200000,
@@ -53016,6 +54025,19 @@
       "cache_read": 0.35
     }
   },
+  "deepinfra/deepseek-ai/DeepSeek-V4.1-Flash": {
+    "name": "DeepSeek V4.1 Flash",
+    "context": 1048576,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
+      "input": 0.2,
+      "output": 0.6,
+      "cache_read": 0.006
+    }
+  },
   "deepinfra/deepseek-ai/DeepSeek-V4-Pro-0813": {
     "name": "DeepSeek V4 Pro 0813",
     "context": 1048576,
@@ -53087,6 +54109,17 @@
       "cache_read": 0.025
     }
   },
+  "deepinfra/google/gemma-3-4b-it": {
+    "name": "Gemma 3 4B IT",
+    "context": 131072,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
+      "input": 0.05,
+      "output": 0.1
+    }
+  },
   "deepinfra/google/gemma-4-31B-it": {
     "name": "Gemma 4 31B IT",
     "context": 262144,
@@ -53112,6 +54145,17 @@
       "output": 0.1
     }
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@@ -59834,6 +61043,19 @@
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@@ -59998,6 +61224,7 @@
   "amazon-bedrock/openai.gpt-oss-safeguard-20b": {
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   "amazon-bedrock/openai.gpt-5.6-luna": {
@@ -60067,27 +61296,42 @@
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@@ -60275,10 +61522,11 @@
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@@ -60310,7 +61558,7 @@
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@@ -60323,6 +61571,7 @@
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@@ -60360,7 +61609,6 @@
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@@ -60433,7 +61681,7 @@
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@@ -60451,18 +61699,18 @@
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@@ -60472,7 +61720,8 @@
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@@ -60552,6 +61801,19 @@
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@@ -60580,13 +61842,13 @@
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@@ -60643,12 +61906,12 @@
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@@ -60690,8 +61953,7 @@
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@@ -60725,6 +61987,7 @@
   "amazon-bedrock/openai.gpt-oss-safeguard-120b": {
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@@ -60785,12 +62048,12 @@
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@@ -60834,7 +62097,8 @@
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@@ -60896,7 +62160,6 @@
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@@ -61093,6 +62356,20 @@
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@@ -61108,7 +62385,7 @@
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@@ -61197,10 +62474,11 @@
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@@ -61209,11 +62487,10 @@
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@@ -61278,10 +62555,11 @@
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@@ -61826,6 +63104,15 @@
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@@ -61953,6 +63240,15 @@
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     "name": "Gemini Embedding 001",
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@@ -62089,6 +63385,15 @@
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+  "merge-gateway/google/gemma-3-12b-it": {
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   "merge-gateway/thinkingmachines/inkling": {
     "name": "Inkling",
     "context": 1048000,
@@ -62313,6 +63618,15 @@
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@@ -62327,13 +63641,13 @@
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@@ -62348,13 +63662,13 @@
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@@ -62556,6 +63870,17 @@
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@@ -63269,9 +64594,9 @@
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@@ -63280,10 +64605,11 @@
     "reasoning": true,
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   "deepseek/deepseek-v4-pro": {
@@ -63298,6 +64624,19 @@
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@@ -66440,9 +67779,9 @@
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@@ -66556,8 +67895,9 @@
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@@ -66999,7 +68339,7 @@
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   "openrouter/~anthropic/claude-haiku-latest": {
-    "name": "Anthropic Claude Haiku Latest",
+    "name": "Claude Haiku Latest",
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@@ -67013,7 +68353,7 @@
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   "openrouter/~anthropic/claude-sonnet-latest": {
-    "name": "Anthropic Claude Sonnet Latest",
+    "name": "Claude Sonnet Latest",
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@@ -67059,9 +68399,9 @@
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   "openrouter/dots-studio/dots-3-note-preview:free": {
@@ -67258,7 +68598,7 @@
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@@ -67468,9 +68808,9 @@
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@@ -67564,6 +68904,7 @@
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@@ -67838,8 +69179,9 @@
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@@ -67868,7 +69210,7 @@
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   "openrouter/google/gemma-3-4b-it": {
-    "name": "Gemma 3 4B",
+    "name": "Gemma 3 4B IT",
     "context": 131072,
     "structured_output": true,
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@@ -68003,7 +69345,7 @@
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   "openrouter/google/gemma-3-27b-it": {
-    "name": "Gemma 3 27B",
+    "name": "Gemma 3 27B IT",
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@@ -68204,7 +69546,7 @@
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   "openrouter/google/gemma-3-12b-it": {
-    "name": "Gemma 3 12B",
+    "name": "Gemma 3 12B IT",
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@@ -68409,8 +69751,8 @@
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@@ -68578,7 +69920,7 @@
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   "openrouter/~google/gemini-pro-latest": {
-    "name": "Google Gemini Pro Latest",
+    "name": "Gemini Pro Latest",
     "context": 1048576,
     "reasoning": true,
     "tool_call": true,
@@ -68593,7 +69935,7 @@
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   "openrouter/~google/gemini-flash-latest": {
-    "name": "Google Gemini Flash Latest",
+    "name": "Gemini Flash Latest",
     "context": 1048576,
     "reasoning": true,
     "tool_call": true,
@@ -68637,6 +69979,19 @@
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+  "openrouter/sakana/fugu-max": {
+    "name": "Fugu Max",
+    "context": 1000000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
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+      "cache_read": 0.25
+    }
+  },
   "openrouter/sakana/sakana-namazu": {
     "name": "Sakana Namazu",
     "context": 262144,
@@ -68650,8 +70005,21 @@
       "cache_read": 0.15
     }
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-    "name": "MoonshotAI Kimi Latest",
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@@ -68659,9 +70027,8 @@
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-    "name": "OpenAI GPT Latest",
+  "openrouter/~openai/gpt-terra-latest": {
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@@ -68872,8 +70251,36 @@
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   "openrouter/~openai/gpt-mini-latest": {
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@@ -68980,6 +70387,32 @@
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@@ -69552,7 +70985,7 @@
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-    "name": "gpt-oss-safeguard-20b",
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@@ -69995,9 +71428,9 @@
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   "openrouter/moonshotai/kimi-k2": {
@@ -70084,6 +71517,24 @@
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@@ -70151,9 +71602,9 @@
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@@ -70318,9 +71769,9 @@
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   "openrouter/z-ai/glm-5v-turbo": {
@@ -70572,6 +72023,19 @@
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@@ -70812,6 +72276,321 @@
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+  "ofox/qwen/qwen3.5-plus": {
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+    "reasoning": true,
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   "ofox/bailian/qwen3.7-max": {
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@@ -71559,7 +73338,7 @@
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@@ -71638,6 +73417,20 @@
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+  "ofox/google/gemini-3.8-flash": {
+    "name": "Gemini 3.8 Flash",
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+    "reasoning": true,
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   "ofox/google/gemini-3.7-flash": {
     "name": "Gemini 3.7 Flash",
     "context": 1048576,
@@ -71683,6 +73476,18 @@
       "cache_write": 1
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+  "ofox/deepseek/deepseek-v4-flash-0423": {
+    "name": "DeepSeek V4 Flash 0423",
+    "context": 1000000,
+    "reasoning": true,
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   "ofox/deepseek/deepseek-v4-flash-vision-exp": {
     "name": "DeepSeek V4 Flash Vision Exp",
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@@ -71732,6 +73537,19 @@
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@@ -71753,7 +73571,7 @@
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@@ -72192,8 +74010,8 @@
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@@ -72202,8 +74020,8 @@
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@@ -72240,8 +74058,8 @@
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+      "output": 0.4,
+      "cache_read": 0.01
     }
   },
   "ofox/z-ai/glm-5": {
@@ -73418,17 +75236,6 @@
       "cache_read": 0
     }
   },
-  "scnet-token-plan/MiMo-V2.5-Pro": {
-    "name": "MiMo-V2.5-Pro",
-    "context": 1048576,
-    "reasoning": true,
-    "tool_call": true,
-    "cost": {
-      "input": 0,
-      "output": 0,
-      "cache_read": 0
-    }
-  },
   "scnet-token-plan/GLM-5": {
     "name": "GLM-5",
     "context": 204800,
@@ -73502,18 +75309,6 @@
       "cache_read": 0
     }
   },
-  "scnet-token-plan/DeepSeek-V3.2": {
-    "name": "DeepSeek V3.2",
-    "context": 128000,
-    "reasoning": true,
-    "tool_call": true,
-    "structured_output": true,
-    "cost": {
-      "input": 0,
-      "output": 0,
-      "cache_read": 0
-    }
-  },
   "scnet-token-plan/DeepSeek-V4-Pro": {
     "name": "DeepSeek V4 Pro",
     "context": 1000000,
@@ -75357,6 +77152,34 @@
       "cache_read": 0
     }
   },
+  "volcengine-coding-plan/kimi-k3": {
+    "name": "Kimi K3",
+    "context": 1048576,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "video": true,
+    "cost": {
+      "input": 0,
+      "output": 0,
+      "cache_read": 0
+    }
+  },
+  "volcengine-coding-plan/glm-5.3-flash": {
+    "name": "GLM-5.3-Flash",
+    "context": 1000000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "video": true,
+    "cost": {
+      "input": 0,
+      "output": 0,
+      "cache_read": 0
+    }
+  },
   "volcengine-coding-plan/doubao-seed-evolving": {
     "name": "Seed Evolving",
     "context": 256000,
@@ -78029,6 +79852,19 @@
       "cache_read": 0.03
     }
   },
+  "togetherai/deepseek-ai/DeepSeek-V4.1-Flash": {
+    "name": "DeepSeek V4.1 Flash",
+    "context": 1048576,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
+      "input": 0.3,
+      "output": 1.2,
+      "cache_read": 0.006
+    }
+  },
   "togetherai/deepseek-ai/DeepSeek-V4-Pro-0813": {
     "name": "DeepSeek V4 Pro 0813",
     "context": 1048576,
@@ -80469,9 +82305,9 @@
     "reasoning": true,
     "tool_call": true,
     "cost": {
-      "input": 0.13,
-      "output": 0.28,
-      "cache_read": 0.03
+      "input": 0.09,
+      "output": 0.17,
+      "cache_read": 0.014
     }
   },
   "cortecs/qwen3.8-flash-next": {
@@ -80568,9 +82404,9 @@
     "structured_output": true,
     "image": true,
     "cost": {
-      "input": 0.334,
-      "output": 2.451,
-      "cache_read": 0.111
+      "input": 0.1,
+      "output": 0.4,
+      "cache_read": 0.04
     }
   },
   "cortecs/claude-opus-5": {
@@ -80962,7 +82798,7 @@
     }
   },
   "cortecs/gemma-3-27b-it": {
-    "name": "gemma-3-27b-it",
+    "name": "Gemma 3 27B IT",
     "context": 131000,
     "reasoning": true,
     "structured_output": true,
@@ -81027,9 +82863,9 @@
     "structured_output": true,
     "image": true,
     "cost": {
-      "input": 0.201,
-      "output": 0.5,
-      "cache_read": 0.05
+      "input": 0.1,
+      "output": 0.35,
+      "cache_read": 0.018
     }
   },
   "cortecs/gpt-4o-mini": {
@@ -81851,6 +83687,17 @@
       "output": 15
     }
   },
+  "nan/glm5.3": {
+    "name": "GLM-5.3",
+    "context": 1000000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "cost": {
+      "input": 0,
+      "output": 0
+    }
+  },
   "nan/qwen3.6": {
     "name": "Qwen3.6 35B-A3B",
     "context": 262144,
@@ -81864,22 +83711,12 @@
     }
   },
   "nan/deepseek-v4-flash": {
-    "name": "DeepSeek V4 Flash",
+    "name": "DeepSeek V4.1 Flash",
     "context": 1000000,
     "reasoning": true,
     "tool_call": true,
     "structured_output": true,
-    "cost": {
-      "input": 0,
-      "output": 0
-    }
-  },
-  "nan/glm5.2": {
-    "name": "GLM-5.2",
-    "context": 500000,
-    "reasoning": true,
-    "tool_call": true,
-    "structured_output": true,
+    "image": true,
     "cost": {
       "input": 0,
       "output": 0
@@ -82950,6 +84787,19 @@
       "cache_read": 0
     }
   },
+  "opencode-go/deepseek-v4.1-flash": {
+    "name": "DeepSeek V4.1 Flash",
+    "context": 1000000,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
+      "input": 0.15,
+      "output": 0.6,
+      "cache_read": 0.003
+    }
+  },
   "opencode-go/hy3": {
     "name": "Hy3",
     "context": 256000,
@@ -83180,19 +85030,6 @@
       "cache_read": 0.26
     }
   },
-  "opencode-go/deepseek-flash": {
-    "name": "DeepSeek V4.1 Flash",
-    "context": 1000000,
-    "reasoning": true,
-    "tool_call": true,
-    "structured_output": true,
-    "image": true,
-    "cost": {
-      "input": 0.15,
-      "output": 0.6,
-      "cache_read": 0.003
-    }
-  },
   "opencode-go/mimo-v2.5": {
     "name": "MiMo V2.5",
     "context": 1000000,
@@ -84005,6 +85842,18 @@
       "cache_read": 0.0375
     }
   },
+  "edenai/groq/openai/gpt-oss-safeguard-20b": {
+    "name": "GPT OSS Safeguard 20B (Groq)",
+    "context": 131072,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "cost": {
+      "input": 0.075,
+      "output": 0.3,
+      "cache_read": 0.0375
+    }
+  },
   "edenai/groq/openai/gpt-oss-120b": {
     "name": "GPT OSS 120B (Groq)",
     "context": 131072,
@@ -84023,8 +85872,17 @@
     "reasoning": true,
     "tool_call": true,
     "cost": {
-      "input": 0.46464,
-      "output": 0.92928
+      "input": 0.46368,
+      "output": 0.92736
+    }
+  },
+  "edenai/scaleway/gemma-3-27b-it": {
+    "name": "Gemma 3 27B IT (Scaleway)",
+    "context": 40000,
+    "image": true,
+    "cost": {
+      "input": 0.287125,
+      "output": 0.57425
     }
   },
   "edenai/scaleway/gpt-oss-120b": {
@@ -84033,8 +85891,8 @@
     "reasoning": true,
     "tool_call": true,
     "cost": {
-      "input": 0.17424,
-      "output": 0.69696
+      "input": 0.17388,
+      "output": 0.69552
     }
   },
   "edenai/scaleway/llama-3.3-70b-instruct": {
@@ -84042,8 +85900,8 @@
     "context": 128000,
     "tool_call": true,
     "cost": {
-      "input": 1.045439,
-      "output": 1.045439
+      "input": 1.04328,
+      "output": 1.04328
     }
   },
   "edenai/nebius/deepseek-ai/DeepSeek-V4-Flash-0731": {
@@ -84094,6 +85952,18 @@
       "cache_read": 0.3
     }
   },
+  "edenai/nebius/google/gemma-3-27b-it": {
+    "name": "Gemma 3 27B IT (Nebius)",
+    "context": 110000,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
+      "input": 0.1,
+      "output": 0.3,
+      "cache_read": 0.1
+    }
+  },
   "edenai/nebius/meta-llama/Llama-3.3-70B-Instruct": {
     "name": "Llama-3.3-70B-Instruct (Nebius)",
     "context": 131072,
@@ -84745,6 +86615,14 @@
       "cache_read": 0.125
     }
   },
+  "edenai/infomaniak/mistralai/Ministral-3-14B-Instruct-2512": {
+    "name": "Ministral 3 14B (Infomaniak)",
+    "context": 100000,
+    "cost": {
+      "input": 0.34776,
+      "output": 0.46368
+    }
+  },
   "edenai/flexai/Nemotron-3-Super-120B-A12B": {
     "name": "Nemotron 3 Super 120B A12B (FlexAI)",
     "context": 262144,
@@ -84989,8 +86867,8 @@
     "structured_output": true,
     "image": true,
     "cost": {
-      "input": 0.3,
-      "output": 1.2,
+      "input": 0.2,
+      "output": 0.6,
       "cache_read": 0.006
     }
   },
@@ -85050,6 +86928,39 @@
       "cache_read": 0.04
     }
   },
+  "edenai/deepinfra/google/gemma-3-4b-it": {
+    "name": "Gemma 3 4B IT (Deep Infra)",
+    "context": 131072,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
+      "input": 0.05,
+      "output": 0.1
+    }
+  },
+  "edenai/deepinfra/google/gemma-3-27b-it": {
+    "name": "Gemma 3 27B IT (Deep Infra)",
+    "context": 131072,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
+      "input": 0.08,
+      "output": 0.16
+    }
+  },
+  "edenai/deepinfra/google/gemma-3-12b-it": {
+    "name": "Gemma 3 12B IT (Deep Infra)",
+    "context": 131072,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
+      "input": 0.05,
+      "output": 0.15
+    }
+  },
   "edenai/deepinfra/zai-org/GLM-4.7-Flash": {
     "name": "GLM-4.7-Flash (Deep Infra)",
     "context": 202752,
@@ -85425,6 +87336,23 @@
       "output": 0.4
     }
   },
+  "edenai/amazon/google.gemma-3-12b-it@us": {
+    "name": "Gemma 3 12B IT (Amazon Bedrock, US)",
+    "context": 128000,
+    "image": true,
+    "cost": {
+      "input": 0.09,
+      "output": 0.29
+    }
+  },
+  "edenai/amazon/mistral.voxtral-mini-3b-2507": {
+    "name": "Voxtral Mini 3B 2507 (Amazon Bedrock)",
+    "context": 128000,
+    "cost": {
+      "input": 0.04,
+      "output": 0.04
+    }
+  },
   "edenai/amazon/amazon.nova-pro-v1:0@us": {
     "name": "Nova Pro (US)",
     "context": 300000,
@@ -85436,6 +87364,24 @@
       "output": 3.2
     }
   },
+  "edenai/amazon/google.gemma-3-12b-it": {
+    "name": "Gemma 3 12B IT (Amazon Bedrock)",
+    "context": 128000,
+    "image": true,
+    "cost": {
+      "input": 0.09,
+      "output": 0.29
+    }
+  },
+  "edenai/amazon/openai.gpt-oss-safeguard-20b": {
+    "name": "GPT OSS Safeguard 20B (Amazon Bedrock)",
+    "context": 128000,
+    "reasoning": true,
+    "cost": {
+      "input": 0.07,
+      "output": 0.2
+    }
+  },
   "edenai/amazon/amazon.nova-lite-v1:0": {
     "name": "Nova Lite",
     "context": 300000,
@@ -85458,6 +87404,15 @@
       "output": 3.2
     }
   },
+  "edenai/amazon/openai.gpt-oss-safeguard-20b@us": {
+    "name": "GPT OSS Safeguard 20B (Amazon Bedrock, US)",
+    "context": 128000,
+    "reasoning": true,
+    "cost": {
+      "input": 0.07,
+      "output": 0.2
+    }
+  },
   "edenai/amazon/moonshot.kimi-k2-thinking": {
     "name": "Kimi K2 Thinking (Amazon Bedrock)",
     "context": 128000,
@@ -85467,6 +87422,15 @@
       "output": 2.5
     }
   },
+  "edenai/amazon/google.gemma-3-27b-it": {
+    "name": "Gemma 3 27B IT (Amazon Bedrock)",
+    "context": 128000,
+    "image": true,
+    "cost": {
+      "input": 0.23,
+      "output": 0.38
+    }
+  },
   "edenai/amazon/amazon.nova-micro-v1:0": {
     "name": "Nova Micro",
     "context": 128000,
@@ -85477,6 +87441,14 @@
       "output": 0.14
     }
   },
+  "edenai/amazon/mistral.voxtral-mini-3b-2507@us": {
+    "name": "Voxtral Mini 3B 2507 (Amazon Bedrock, US)",
+    "context": 128000,
+    "cost": {
+      "input": 0.04,
+      "output": 0.04
+    }
+  },
   "edenai/amazon/mistral.pixtral-large-2502-v1:0@us": {
     "name": "Pixtral Large (25.02) (Amazon Bedrock, US)",
     "context": 128000,
@@ -85486,6 +87458,15 @@
       "output": 6
     }
   },
+  "edenai/amazon/google.gemma-3-27b-it@us": {
+    "name": "Gemma 3 27B IT (Amazon Bedrock, US)",
+    "context": 128000,
+    "image": true,
+    "cost": {
+      "input": 0.23,
+      "output": 0.38
+    }
+  },
   "edenai/amazon/zai.glm-4.7-flash": {
     "name": "GLM-4.7-Flash (Amazon Bedrock)",
     "context": 200000,
@@ -85496,6 +87477,40 @@
       "output": 0.4
     }
   },
+  "edenai/amazon/google.gemma-3-4b-it": {
+    "name": "Gemma 3 4B IT (Amazon Bedrock)",
+    "context": 128000,
+    "image": true,
+    "cost": {
+      "input": 0.04,
+      "output": 0.08
+    }
+  },
+  "edenai/amazon/mistral.voxtral-small-24b-2507": {
+    "name": "Voxtral Small 24B 2507 (Amazon Bedrock)",
+    "context": 128000,
+    "cost": {
+      "input": 0.1,
+      "output": 0.3
+    }
+  },
+  "edenai/amazon/mistral.voxtral-small-24b-2507@us": {
+    "name": "Voxtral Small 24B 2507 (Amazon Bedrock, US)",
+    "context": 128000,
+    "cost": {
+      "input": 0.1,
+      "output": 0.3
+    }
+  },
+  "edenai/amazon/google.gemma-3-4b-it@us": {
+    "name": "Gemma 3 4B IT (Amazon Bedrock, US)",
+    "context": 128000,
+    "image": true,
+    "cost": {
+      "input": 0.04,
+      "output": 0.08
+    }
+  },
   "edenai/openai/gpt-5-nano": {
     "name": "GPT-5 Nano",
     "context": 400000,
@@ -85758,8 +87773,7 @@
     "image": true,
     "cost": {
       "input": 30,
-      "output": 180,
-      "cache_read": 3
+      "output": 180
     }
   },
   "edenai/openai/gpt-5.4-mini": {
@@ -85807,8 +87821,7 @@
     "image": true,
     "cost": {
       "input": 30,
-      "output": 180,
-      "cache_read": 3
+      "output": 180
     }
   },
   "edenai/openai/gpt-5.6-terra": {
@@ -85908,8 +87921,7 @@
     "image": true,
     "cost": {
       "input": 30,
-      "output": 180,
-      "cache_read": 3
+      "output": 180
     }
   },
   "edenai/openai/o3": {
@@ -86227,6 +88239,19 @@
       "cache_read": 0.03
     }
   },
+  "edenai/together_ai/deepseek-ai/DeepSeek-V4.1-Flash": {
+    "name": "DeepSeek V4.1 Flash (Together AI)",
+    "context": 1048576,
+    "reasoning": true,
+    "tool_call": true,
+    "structured_output": true,
+    "image": true,
+    "cost": {
+      "input": 0.3,
+      "output": 1.2,
+      "cache_read": 0.006
+    }
+  },
   "edenai/together_ai/deepseek-ai/DeepSeek-V4-Pro-0813": {
     "name": "DeepSeek V4 Pro 0813 (Together AI)",
     "context": 1048576,
@@ -86835,8 +88860,8 @@
     "name": "Llama-3.3-70B-Instruct (IONOS)",
     "context": 128000,
     "cost": {
-      "input": 0.75504,
-      "output": 0.75504
+      "input": 0.75348,
+      "output": 0.75348
     }
   },
   "edenai/ionos/openai/gpt-oss-120b": {
@@ -86844,8 +88869,8 @@
     "context": 131072,
     "reasoning": true,
     "cost": {
-      "input": 0.17424,
-      "output": 0.75504
+      "input": 0.17388,
+      "output": 0.75348
     }
   },
   "edenai/perplexityai/sonar": {
diff --git a/src/types/sessions.ts b/src/types/sessions.ts
index 2d3c8ce..33204b4 100644
--- a/src/types/sessions.ts
+++ b/src/types/sessions.ts
@@ -39,6 +39,12 @@ export interface ActionResponse {
   deleted?: boolean | null;
 }
 
+export interface BulkArchiveResult {
+  archived: number;
+  skipped: number;
+  errors: string[];
+}
+
 export interface PreviewMessage {
   role: string;
   time: number | null;