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+ "cost": { + "input": 0.3, + "output": 1.2, + "cache_read": 0.03, + "cache_write": 0.375 + } + }, + "minimax-cn/MiniMax-M2.5-highspeed": { + "name": "MiniMax-M2.5-highspeed", + "context": 204800, + "reasoning": true, + "tool_call": true, + "cost": { + "input": 0.6, + "output": 2.4, + "cache_read": 0.06, + "cache_write": 0.375 + } + }, + "minimax-cn/MiniMax-M2.7-highspeed": { + "name": "MiniMax-M2.7-highspeed", + "context": 204800, + "reasoning": true, + "tool_call": true, + "cost": { + "input": 0.6, + "output": 2.4, + "cache_read": 0.06, + "cache_write": 0.375 + } + }, + "minimax-cn/MiniMax-M3": { + "name": "MiniMax-M3", + "context": 1000000, + "reasoning": true, + "tool_call": true, + "image": true, + "video": true, + "cost": { + "input": 0.3, + "output": 1.2, + "cache_read": 0.06 + } + }, + "ebcloud/Kimi-K2.6": { + "name": "Kimi K2.6", + "context": 262144, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "cost": { + "input": 0.9286, + "output": 3.8571 + } + }, + "ebcloud/DeepSeek-V4-Flash": { + "name": "DeepSeek V4 Flash", + "context": 1000000, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "cost": { + "input": 0.143, + "output": 0.2857 + } + }, + "ebcloud/GLM-5.1": { + "name": "GLM-5.1", + "context": 200000, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "cost": { + "input": 0.8571, + "output": 3.4286 + } + }, + "ebcloud/DeepSeek-V4-Pro": { + "name": "DeepSeek V4 Pro", + "context": 1000000, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "cost": { + "input": 0.4286, + "output": 0.8571 + } + }, + "databricks/databricks-gpt-5-nano": { + "name": "GPT-5 Nano", + "context": 400000, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "image": true, + "cost": { + "input": 0.05, + "output": 0.4, + "cache_read": 0.005 + } + }, + "databricks/databricks-gemini-3-1-flash-lite": { + "name": "Gemini 3.1 Flash Lite Preview", + "context": 1048576, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "image": true, + "video": true, + "cost": { + "input": 0.25, + "output": 1.5, + "cache_read": 0.025 + } + }, + "databricks/databricks-gpt-oss-120b": { + "name": "GPT OSS 120B", + "context": 131072, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "cost": { + "input": 0.072, + "output": 0.28 + } + }, + "databricks/databricks-claude-opus-4-5": { + "name": "Claude Opus 4.5 (latest)", + "context": 200000, + "reasoning": true, + "tool_call": true, + "image": true, + "cost": { + "input": 5, + "output": 25, + "cache_read": 0.5, + "cache_write": 6.25 + } + }, + "databricks/databricks-claude-sonnet-4-6": { + "name": "Claude Sonnet 4.6", + "context": 1000000, + "reasoning": true, + "tool_call": true, + "image": true, + "cost": { + "input": 3, + "output": 15, + "cache_read": 0.3, + "cache_write": 3.75 + } + }, + "databricks/databricks-claude-sonnet-4": { + "name": "Claude Sonnet 4.5", + "context": 200000, + "reasoning": true, + "tool_call": true, + "image": true, + "cost": { + "input": 3, + "output": 15, + "cache_read": 0.3, + "cache_write": 3.75 + } + }, + "databricks/databricks-gemini-3-flash": { + "name": "Gemini 3 Flash Preview", + "context": 1048576, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "image": true, + "video": true, + "cost": { + "input": 0.5, + "output": 3, + "cache_read": 0.05 + } + }, + "databricks/databricks-gpt-oss-20b": { + "name": "GPT OSS 20B", + "context": 131072, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "cost": { + "input": 0.05, + "output": 0.2 + } + }, + "databricks/databricks-glm-5-2": { + "name": "GLM-5.2", + "context": 1000000, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "cost": { + "input": 1.4, + "output": 4.4, + "cache_read": 0.26 + } + }, + "databricks/databricks-claude-opus-4-7": { + "name": "Claude Opus 4.7", + "context": 1000000, + "reasoning": true, + "tool_call": true, + "image": true, + "cost": { + "input": 5, + "output": 25, + "cache_read": 0.5, + "cache_write": 6.25 + } + }, + "databricks/databricks-gpt-5-6-sol": { + "name": "GPT-5.6 Sol", + "context": 1050000, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "image": true, + "cost": { + "input": 5, + "output": 30, + "cache_read": 0.5 + } + }, + "databricks/databricks-gpt-5-4-nano": { + "name": "GPT-5.4 nano", + "context": 400000, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "image": true, + "cost": { + "input": 0.2, + "output": 1.25, + "cache_read": 0.02 + } + }, + "databricks/databricks-gemini-2-5-pro": { + "name": "Gemini 2.5 Pro", + "context": 1048576, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "image": true, + "video": true, + "cost": { + "input": 1.25, + "output": 10, + "cache_read": 0.125 + } + }, + "databricks/databricks-gpt-5-6-terra": { + "name": "GPT-5.6 Terra", + "context": 1050000, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "image": true, + "cost": { + "input": 2.5, + "output": 15, + "cache_read": 0.25 + } + }, + "databricks/databricks-gpt-5-5": { + "name": "GPT-5.5", + "context": 1050000, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "image": true, + "cost": { + "input": 5, + "output": 30, + "cache_read": 0.5 + } + }, + "databricks/databricks-gpt-5-2": { + "name": "GPT-5.2", + "context": 400000, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "image": true, + "cost": { + "input": 1.75, + "output": 14, + "cache_read": 0.175 + } + }, + "databricks/databricks-gemini-3-1-pro": { + "name": "Gemini 3.1 Pro Preview Custom Tools", + "context": 1048576, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "image": true, + "video": true, + "cost": { + "input": 2, + "output": 12, + "cache_read": 0.2 + } + }, + "databricks/databricks-claude-sonnet-4-5": { + "name": "Claude Sonnet 4.5 (latest)", + "context": 200000, + "reasoning": true, + "tool_call": true, + "image": true, + "cost": { + "input": 3, + "output": 15, + "cache_read": 0.3, + "cache_write": 3.75 + } + }, + "databricks/databricks-claude-haiku-4-5": { + "name": "Claude Haiku 4.5 (latest)", + "context": 200000, + "reasoning": true, + "tool_call": true, + "image": true, + "cost": { + "input": 1, + "output": 5, + "cache_read": 0.1, + "cache_write": 1.25 + } + }, + "databricks/databricks-kimi-k2-7-code": { + "name": "Kimi K2.7 Code", + "context": 262144, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "image": true, + "video": true, + "cost": { + "input": 0.95, + "output": 4, + "cache_read": 0.19 + } + }, + "databricks/databricks-claude-opus-4-1": { + "name": "Claude Opus 4.1 (latest)", + "context": 200000, + "reasoning": true, + "tool_call": true, + "image": true, + "cost": { + "input": 15, + "output": 75, + "cache_read": 1.5, + "cache_write": 18.75 + } + }, + "databricks/databricks-gemini-3-pro": { + "name": "Gemini 3 Pro Preview", + "context": 1048576, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "image": true, + "video": true, + "cost": { + "input": 2, + "output": 12, + "cache_read": 0.2 + } + }, + "databricks/databricks-gemini-2-5-flash": { + "name": "Gemini 2.5 Flash", + "context": 1048576, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "image": true, + "video": true, + "cost": { + "input": 0.3, + "output": 2.5, + "cache_read": 0.03 + } + }, + "databricks/databricks-claude-opus-4-6": { + "name": "Claude Opus 4.6", + "context": 1000000, + "reasoning": true, + "tool_call": true, + "image": true, + "cost": { + "input": 5, + "output": 25, + "cache_read": 0.5, + "cache_write": 6.25 + } + }, + "databricks/databricks-gpt-5-1": { + "name": "GPT-5.1", + "context": 400000, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "image": true, + "cost": { + "input": 1.25, + "output": 10, + "cache_read": 0.125 + } + }, + "databricks/databricks-gpt-5-4-mini": { + "name": "GPT-5.4 mini", + "context": 400000, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "image": true, + "cost": { + "input": 0.75, + "output": 4.5, + "cache_read": 0.075 + } + }, + "databricks/databricks-gpt-5-6-luna": { + "name": "GPT-5.6 Luna", + "context": 400000, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "image": true, + "cost": { + "input": 1, + "output": 6, + "cache_read": 0.1 + } + }, + "databricks/databricks-gpt-5": { + "name": "GPT-5", + "context": 400000, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "image": true, + "cost": { + "input": 1.25, + "output": 10, + "cache_read": 0.125 + } + }, + "databricks/databricks-gpt-5-4": { + "name": "GPT-5.4", + "context": 1050000, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "image": true, + "cost": { + "input": 2.5, + "output": 15, + "cache_read": 0.25 + } + }, + "databricks/databricks-gpt-5-mini": { + "name": "GPT-5 Mini", + "context": 400000, + "reasoning": true, + "tool_call": true, + "structured_output": true, + "image": true, + "cost": { + "input": 0.25, + "output": 2, + "cache_read": 0.025 + } + }, + "minimax-cn-coding-plan/MiniMax-M2": { + "name": "MiniMax-M2", + "context": 196608, + "reasoning": true, + "tool_call": true, + "cost": { + "input": 0, + "output": 0 + } + }, + "minimax-cn-coding-plan/MiniMax-M2.7": { + "name": "MiniMax-M2.7", + "context": 204800, + "reasoning": true, + "tool_call": true, + "cost": { + "input": 0, + "output": 0, + "cache_read": 0, + "cache_write": 0 + } + }, + "minimax-cn-coding-plan/MiniMax-M2.1": { + "name": "MiniMax-M2.1", + "context": 204800, + "reasoning": true, + "tool_call": true, + "cost": { + "input": 0, + "output": 0 + } + }, + "minimax-cn-coding-plan/MiniMax-M2.5": { + "name": "MiniMax-M2.5", + "context": 204800, + "reasoning": true, + "tool_call": true, + "cost": { + "input": 0, + "output": 0, + "cache_read": 0, + "cache_write": 0 + } + }, + "minimax-cn-coding-plan/MiniMax-M2.5-highspeed": { + "name": "MiniMax-M2.5-highspeed", + "context": 204800, + "reasoning": true, + "tool_call": true, + "cost": { + "input": 0, + "output": 0, + "cache_read": 0, + "cache_write": 0 + } + }, + "minimax-cn-coding-plan/MiniMax-M2.7-highspeed": { + "name": "MiniMax-M2.7-highspeed", + "context": 204800, + "reasoning": true, + "tool_call": true, + "cost": { + "input": 0, + "output": 0, + "cache_read": 0, + "cache_write": 0 + } + }, + "minimax-cn-coding-plan/MiniMax-M3": { + "name": "MiniMax-M3", + "context": 1000000, + "reasoning": true, + "tool_call": true, + "image": true, + "video": true, + "cost": { + "input": 0, + "output": 0, + "cache_read": 0, + "cache_write": 0 + } + } +} diff --git a/src-tauri/src/dashboard.rs b/src-tauri/src/dashboard.rs index bfbf05b..f678796 100644 --- a/src-tauri/src/dashboard.rs +++ b/src-tauri/src/dashboard.rs @@ -530,6 +530,15 @@ fn models_dev_cost_index() -> &'static HashMap { }) } +/// Warm the compiled-in models.dev price index off the first dashboard open: +/// parsing the ~1.3 MB snapshot costs tens of milliseconds, so build it on a +/// background thread at startup instead of lazily on the first get_summary. +pub fn warm_price_index() { + std::thread::spawn(|| { + let _ = models_dev_cost_index(); + }); +} + /// Official providers take precedence over resellers when the same model id /// ships under multiple providers and no provider prefix disambiguates. const OFFICIAL_PROVIDERS: &[&str] = &[ @@ -743,6 +752,45 @@ fn scan_usage(home: &Path) -> (Vec, ScanMeta) { }) } +// --------------------------------------------------------------------------- +// Scan cache +// --------------------------------------------------------------------------- + +/// Short-TTL cache for the expensive `scan_usage` walk (reads every +/// wire.jsonl under the sessions root and prices every record). Tab switches +/// call get_summary repeatedly; re-walking the whole tree on every switch is +/// the main dashboard lag. Keyed by home, expires after 8s; `refresh=true` +/// bypasses it. +struct SummaryCacheEntry { + home: String, + scanned_at: std::time::Instant, + records: Vec, + meta: ScanMeta, +} + +static SUMMARY_CACHE: Mutex> = Mutex::new(None); +const SUMMARY_CACHE_TTL: std::time::Duration = std::time::Duration::from_secs(8); + +fn scan_usage_cached(home: &Path, refresh: bool) -> (Vec, ScanMeta) { + let home_s = home.to_string_lossy().to_string(); + let mut cache = SUMMARY_CACHE.lock().unwrap(); + let hit = cache + .as_ref() + .is_some_and(|e| !refresh && e.home == home_s && e.scanned_at.elapsed() < SUMMARY_CACHE_TTL); + if hit { + let e = cache.as_ref().unwrap(); + return (e.records.clone(), e.meta.clone()); + } + let (records, meta) = scan_usage(home); + *cache = Some(SummaryCacheEntry { + home: home_s, + scanned_at: std::time::Instant::now(), + records: records.clone(), + meta: meta.clone(), + }); + (records, meta) +} + // --------------------------------------------------------------------------- // Aggregate // --------------------------------------------------------------------------- @@ -1489,13 +1537,13 @@ pub fn get_prices() -> PricesResult { #[tauri::command] pub fn get_summary(home_override: Option, range: Option, refresh: Option) -> SummaryResult { - let _refresh = refresh.unwrap_or(false); + let refresh = refresh.unwrap_or(false); let home = resolve_kimi_home(home_override); let now_ms = std::time::SystemTime::now() .duration_since(std::time::UNIX_EPOCH).unwrap_or_default().as_millis() as u64; let r = range.unwrap_or_else(|| "30d".into()); - let (records, meta) = scan_usage(&home); + let (records, meta) = scan_usage_cached(&home, refresh); let stats = aggregate(&records, &r, now_ms); let all_stats = aggregate(&records, "all", now_ms); let heatmap = build_heatmap(&records, now_ms); diff --git a/src-tauri/src/lib.rs b/src-tauri/src/lib.rs index ce58f72..74d9dd8 100644 --- a/src-tauri/src/lib.rs +++ b/src-tauri/src/lib.rs @@ -27,6 +27,8 @@ pub fn run() { .plugin(tauri_plugin_opener::init()) .setup(|app| { println!("[Tauri] Setup started"); + // Build the models.dev price index off the first dashboard query. + dashboard::warm_price_index(); let window = app.get_webview_window("main").unwrap(); println!("[Tauri] Window label: {}", window.label()); diff --git a/src/App.tsx b/src/App.tsx index 40b8c96..a0c29c4 100644 --- a/src/App.tsx +++ b/src/App.tsx @@ -1,4 +1,4 @@ -import { useCallback, useEffect, useMemo, useState } from "react"; +import { useCallback, useEffect, useMemo, useReducer, useState } from "react"; import { invoke } from "@tauri-apps/api/core"; import { getCurrentWindow } from "@tauri-apps/api/window"; import { useConfig } from "./hooks/useConfig"; @@ -12,7 +12,7 @@ import { UsageConfigModal } from "./components/UsageConfigModal"; import { PresetPickerModal } from "./components/PresetPickerModal"; import { useTranslation } from "./i18n"; import { getDefaultMaxContextSize } from "./lib/model-defaults"; -import { getModelRef } from "./lib/models-dev"; +import { getModelRef, modelsDevReady, onModelsDevReady } from "./lib/models-dev"; import { presetToProviderAndModels, type ProviderPreset, @@ -121,6 +121,14 @@ export default function App() { }).catch(() => {}); }, [loading, config, agent]); + // Load the models.dev index in the background (not in the main bundle) + // and re-render once it lands so context/capability columns fill in. + const [, forceModelsDevReady] = useReducer((x: number) => x + 1, 0); + useEffect(() => { + onModelsDevReady(forceModelsDevReady); + void modelsDevReady(); + }, []); + const providers = useMemo( () => (config ? Object.values(config.providers) : []), [config] diff --git a/src/components/dashboard/DashboardPage.tsx b/src/components/dashboard/DashboardPage.tsx index 7811081..acc6636 100644 --- a/src/components/dashboard/DashboardPage.tsx +++ b/src/components/dashboard/DashboardPage.tsx @@ -71,7 +71,7 @@ export function DashboardPage() {
{t("dashLoadFailed")}
{error}