merge: Dev_20260801 → main(v0.6.9:仪表盘缓存命中列 + 人民币计价 + 性能优化)
Release / Version consistency (push) Canceled after 0s
Release / Build (macos-latest) (push) Canceled after 0s
Release / Build (ubuntu-latest) (push) Canceled after 0s
Release / Build (windows-latest) (push) Canceled after 0s

This commit is contained in:
KimiSwitch Dev committed 2026-08-02 00:18:49 +08:00
commit acde6d97c2
20 files changed
+1092 -174

No files matched your search

+1 -1
View File
@@ -1,7 +1,7 @@
{
"name": "kimiswitch",
"private": true,
"version": "0.6.8",
"version": "0.6.9",
"type": "module",
"scripts": {
"dev": "vite",
+1 -1
View File
@@ -1,6 +1,6 @@
[package]
name = "kimiswitch"
version = "0.6.8"
version = "0.6.9"
description = "Kimi Switch - model config manager"
authors = ["you"]
edition = "2021"
+30
View File
@@ -610,7 +610,26 @@ fn strip_context_suffix(model_name: &str) -> Option<String> {
})
}
/// Memoized price resolution. `match_price` is called once per usage record
/// during the scan, and the models.dev suffix scan is O(5910) per miss — with
/// thousands of records sharing a handful of model names, memoizing the result
/// turns the whole scan from O(records × 5910) into O(unique_models × 5910).
static MATCH_PRICE_MEMO: OnceLock<Mutex<HashMap<String, (String, f64, f64, f64, bool)>>> =
OnceLock::new();
/// Resolve a model's price, caching per-model results (hits and misses).
fn match_price(model_name: &str) -> (String, f64, f64, f64, bool) {
let key = model_name.to_ascii_lowercase();
let memo = MATCH_PRICE_MEMO.get_or_init(|| Mutex::new(HashMap::new()));
if let Some(hit) = memo.lock().unwrap().get(&key) {
return hit.clone();
}
let result = match_price_inner(model_name);
memo.lock().unwrap().insert(key, result.clone());
result
}
fn match_price_inner(model_name: &str) -> (String, f64, f64, f64, bool) {
let bare = match model_name.rsplit_once('/') {
Some((_, b)) => b,
None => model_name,
@@ -1537,6 +1556,7 @@ pub fn get_prices() -> PricesResult {
#[tauri::command]
pub fn get_summary(home_override: Option<String>, range: Option<String>, refresh: Option<bool>) -> SummaryResult {
let t0 = std::time::Instant::now();
let refresh = refresh.unwrap_or(false);
let home = resolve_kimi_home(home_override);
let now_ms = std::time::SystemTime::now()
@@ -1544,6 +1564,7 @@ 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 t1 = std::time::Instant::now();
let stats = aggregate(&records, &r, now_ms);
let all_stats = aggregate(&records, "all", now_ms);
let heatmap = build_heatmap(&records, now_ms);
@@ -1568,6 +1589,15 @@ pub fn get_summary(home_override: Option<String>, range: Option<String>, refresh
name, provider: std::env::var("KIMI_MODEL_PROVIDER").ok(), model: std::env::var("KIMI_MODEL_ID").ok(),
});
let t2 = std::time::Instant::now();
let scan_ms = t1.duration_since(t0).as_secs_f64() * 1000.0;
let aggregate_ms = t2.duration_since(t1).as_secs_f64() * 1000.0;
let total_ms = t2.duration_since(t0).as_secs_f64() * 1000.0;
eprintln!(
"[dashboard] get_summary range={} records={} scan={:.0}ms aggregate={:.0}ms total={:.0}ms",
r, records.len(), scan_ms, aggregate_ms, total_ms
);
SummaryResult {
home: home.to_string_lossy().to_string(),
valid: is_kimi_home(&home),
+1 -1
View File
@@ -1,6 +1,6 @@
{
"productName": "Kimi Switch",
"version": "0.6.8",
"version": "0.6.9",
"identifier": "com.kimiswitch.app",
"build": {
"beforeDevCommand": "npm run dev",
+4 -2
View File
@@ -1,7 +1,8 @@
import { useMemo, useState } from "react";
import { createPortal } from "react-dom";
import { useTranslation } from "../../i18n";
import { fmtPct, fmtTokens, fmtUsd } from "../../lib/dashboard-format";
import { useCurrency } from "../../hooks/useCurrency";
import { fmtPct, fmtTokens } from "../../lib/dashboard-format";
import type { DailyRow } from "../../types/dashboard";
import { DailyDetailModal } from "./DailyDetailModal";
@@ -43,6 +44,7 @@ function shortModel(model: string): string {
export function DailyBars({ daily, dimension, names, unknownProviderLabel }: DailyBarsProps) {
const { t } = useTranslation();
const { money } = useCurrency();
const [selected, setSelected] = useState<DailyRow | null>(null);
const colorMap = useMemo(() => {
@@ -103,7 +105,7 @@ export function DailyBars({ daily, dimension, names, unknownProviderLabel }: Dai
const tooltipLines = [
d.date,
`${t("totalTokens")}: ${fmtTokens(d.totalTokens)} · ${fmtUsd(d.costUsd)} · ${t("colCacheHit")} ${fmtPct(d.cacheHitRate)}`,
`${t("totalTokens")}: ${fmtTokens(d.totalTokens)} · ${money(d.costUsd)} · ${t("colCacheHit")} ${fmtPct(d.cacheHitRate)}`,
...segments.map((s) => `${displayName(s.key)}: ${fmtTokens(s.tokens)}`),
"",
t("doubleClickHint"),
@@ -1,6 +1,7 @@
import { useEffect } from "react";
import { useTranslation } from "../../i18n";
import { fmtPct, fmtTokens, fmtUsd } from "../../lib/dashboard-format";
import { useCurrency } from "../../hooks/useCurrency";
import { fmtPct, fmtTokens } from "../../lib/dashboard-format";
import type { DailyRow } from "../../types/dashboard";
import { modelColor } from "./DailyBars";
@@ -22,6 +23,7 @@ function shortModel(model: string): string {
export function DailyDetailModal({ day, dimension, colorMap, unknownProviderLabel, onClose }: DailyDetailModalProps) {
const { t } = useTranslation();
const { money } = useCurrency();
useEffect(() => {
const onKey = (e: KeyboardEvent) => {
@@ -106,7 +108,7 @@ export function DailyDetailModal({ day, dimension, colorMap, unknownProviderLabe
{/* Day summary chips */}
<div className="grid grid-cols-2 gap-2 px-5 py-3 sm:grid-cols-4">
<SummaryChip label={t("totalTokens")} value={fmtTokens(day.totalTokens)} tone="default" />
<SummaryChip label={t("cost")} value={fmtUsd(day.costUsd)} tone="orange" />
<SummaryChip label={t("cost")} value={money(day.costUsd)} tone="orange" />
<SummaryChip label={t("requests")} value={Math.round(day.requests).toLocaleString()} tone="blue" />
<SummaryChip label={t("cacheHitRate")} value={fmtPct(day.cacheHitRate)} tone="green" />
</div>
+23 -6
View File
@@ -1,13 +1,20 @@
import { useState, type ReactNode } from "react";
import { useDashboard, type DashboardRange } from "../../hooks/useDashboard";
import { useCurrency } from "../../hooks/useCurrency";
import { useTranslation } from "../../i18n";
import { fmtInt, fmtPct, fmtTime, fmtTokens, fmtUsd } from "../../lib/dashboard-format";
import { fmtInt, fmtPct, fmtTime, fmtTokens } from "../../lib/dashboard-format";
import { DailyBars } from "./DailyBars";
import { Heatmap } from "./Heatmap";
import { TrendLineChart } from "./TrendLineChart";
const RANGES: DashboardRange[] = ["today", "7d", "30d", "all"];
/** Per-request cache hit rate: cached tokens / total input tokens. */
function cacheHitOf(r: { inputOther: number; inputCacheRead: number }): number {
const denom = r.inputOther + r.inputCacheRead;
return denom > 0 ? r.inputCacheRead / denom : 0;
}
function Card({
title,
subtitle,
@@ -44,7 +51,8 @@ function KpiCard({ label, value, sub }: { label: string; value: string; sub?: st
export function DashboardPage() {
const { t } = useTranslation();
const { range, changeRange, data, loading, error, refresh } = useDashboard();
const { money } = useCurrency();
const { range, changeRange, data, loading, error, refresh, loadStats } = useDashboard();
const [showAllModels, setShowAllModels] = useState(false);
const [recentPage, setRecentPage] = useState(1);
const [trendTab, setTrendTab] = useState<"daily" | "model" | "provider">("daily");
@@ -120,13 +128,14 @@ export function DashboardPage() {
{ label: t("kpiCacheCreation"), value: fmtTokens(totals.inputCacheCreation), sub: fmtInt(totals.inputCacheCreation) },
{ label: t("kpiCacheHit"), value: fmtPct(totals.cacheHitRate) },
{ label: t("totalTokens"), value: fmtTokens(totals.totalTokens), sub: fmtInt(totals.totalTokens) },
{ label: t("kpiCost"), value: fmtUsd(totals.costUsd) },
{ label: t("kpiCost"), value: money(totals.costUsd) },
];
return (
<div className="h-full overflow-auto p-4 space-y-4">
{/* Range tabs + refresh */}
<div className="flex items-center justify-between">
<div className="flex items-center gap-3">
<div className="flex items-center bg-input border border-border rounded p-0.5">
{RANGES.map((r) => (
<button
@@ -143,6 +152,12 @@ export function DashboardPage() {
</button>
))}
</div>
{loadStats && !loading && (
<span className="hidden text-[10px] text-content-muted sm:inline">
{t("loadStats", { ms: loadStats.ms, kb: loadStats.kb })}
</span>
)}
</div>
<button
type="button"
onClick={() => refresh(true)}
@@ -175,7 +190,7 @@ export function DashboardPage() {
{fmtTokens(tot.totalTokens)}
</div>
<div className="mt-1 text-[11px] text-content-muted">
{fmtInt(tot.requests)} {t("unitTimes")} · {fmtUsd(tot.costUsd)} · {fmtPct(tot.cacheHitRate)}
{fmtInt(tot.requests)} {t("unitTimes")} · {money(tot.costUsd)} · {fmtPct(tot.cacheHitRate)}
</div>
</button>
);
@@ -305,7 +320,7 @@ export function DashboardPage() {
<td className="py-2 pr-3 text-right text-content-muted">{fmtInt(m.requests)}</td>
<td className="py-2 pr-3 text-right text-content-muted">{fmtTokens(m.totalTokens)}</td>
<td className="py-2 pr-3 text-right text-content-muted">{fmtPct(m.cacheHitRate)}</td>
<td className="py-2 text-right text-orange-600 dark:text-orange-400">{fmtUsd(m.costUsd)}</td>
<td className="py-2 text-right text-orange-600 dark:text-orange-400">{money(m.costUsd)}</td>
</tr>
))}
</tbody>
@@ -346,6 +361,7 @@ export function DashboardPage() {
<th className="pb-2 pr-4 font-normal text-right">{t("colInput")}</th>
<th className="pb-2 pr-4 font-normal text-right">{t("colOutput")}</th>
<th className="pb-2 pr-4 font-normal text-right">{t("colCacheRead")}</th>
<th className="pb-2 pr-4 font-normal text-right">{t("colCacheHit")}</th>
<th className="pb-2 font-normal text-right">{t("cost")}</th>
</tr>
</thead>
@@ -359,7 +375,8 @@ export function DashboardPage() {
<td className="py-1.5 pr-4 text-right text-content-muted">{fmtTokens(r.inputOther)}</td>
<td className="py-1.5 pr-4 text-right text-content-muted">{fmtTokens(r.output)}</td>
<td className="py-1.5 pr-4 text-right text-content-muted">{fmtTokens(r.inputCacheRead)}</td>
<td className="py-1.5 text-right text-orange-600 dark:text-orange-400">{fmtUsd(r.costUsd)}</td>
<td className="py-1.5 pr-4 text-right text-content-muted">{fmtPct(cacheHitOf(r))}</td>
<td className="py-1.5 text-right text-orange-600 dark:text-orange-400">{money(r.costUsd)}</td>
</tr>
))}
</tbody>
+4 -2
View File
@@ -1,7 +1,8 @@
import { useEffect, useMemo, useRef, useState, type MouseEvent } from "react";
import { createPortal } from "react-dom";
import { useTranslation } from "../../i18n";
import { fmtPct, fmtTokens, fmtUsd } from "../../lib/dashboard-format";
import { useCurrency } from "../../hooks/useCurrency";
import { fmtPct, fmtTokens } from "../../lib/dashboard-format";
import type { HeatmapCell, HeatmapData } from "../../types/dashboard";
interface HeatmapProps {
@@ -220,6 +221,7 @@ export function Heatmap({ heatmap }: HeatmapProps) {
function HeatmapTooltip({ state }: { state: HoverState }) {
const { t } = useTranslation();
const { money } = useCurrency();
const { cell, x, y } = state;
// Position above the cursor with a small offset; flip below if too close to top.
const offset = 14;
@@ -239,7 +241,7 @@ function HeatmapTooltip({ state }: { state: HoverState }) {
>
<div className="font-medium text-content-primary">{cell.date}</div>
<div className="text-content-muted">
{fmtTokens(cell.totalTokens)} · {fmtUsd(cell.costUsd)} ·{" "}
{fmtTokens(cell.totalTokens)} · {money(cell.costUsd)} ·{" "}
{fmtInt(cell.requests)} {t("requests")}
</div>
<div className="text-content-muted">
+83
View File
@@ -0,0 +1,83 @@
import { useCallback, useEffect, useState } from "react";
import { useTranslation } from "../i18n";
import { fmtUsd } from "../lib/dashboard-format";
/**
* USD → CNY exchange rate for the dashboard.
* Chinese mode shows prices in CNY (latest available rate), English stays in
* USD. The rate is fetched once and cached in localStorage for 12h; any
* failure falls back to a conservative fixed rate so the UI never blocks.
*/
const FALLBACK_RATE = 7.2;
const CACHE_KEY = "kimi-switch-cny-rate";
const CACHE_TTL = 12 * 60 * 60 * 1000; // 12 hours
function readCachedRate(): number | null {
try {
const raw = localStorage.getItem(CACHE_KEY);
if (!raw) return null;
const { ts, rate } = JSON.parse(raw) as { ts: number; rate: number };
if (Date.now() - ts > CACHE_TTL || !(rate > 1)) return null;
return rate;
} catch {
return null;
}
}
function writeCachedRate(rate: number) {
try {
localStorage.setItem(CACHE_KEY, JSON.stringify({ ts: Date.now(), rate }));
} catch {
/* ignore */
}
}
export function useCurrency() {
const { lang } = useTranslation();
const [rate, setRate] = useState<number | null>(null);
useEffect(() => {
let cancelled = false;
(async () => {
const cached = readCachedRate();
if (cached) {
setRate(cached);
return;
}
try {
const res = await fetch("https://open.er-api.com/v6/latest/USD");
if (res.ok) {
const data = (await res.json()) as { rates?: { CNY?: number } };
const cny = Number(data.rates?.CNY);
if (cny > 1) {
if (!cancelled) setRate(cny);
writeCachedRate(cny);
return;
}
}
} catch {
/* network blocked → fallback */
}
if (!cancelled) setRate(FALLBACK_RATE);
})();
return () => {
cancelled = true;
};
}, []);
/** Format a USD cost for display: CNY in Chinese mode, USD otherwise. */
const money = useCallback(
(usd: number): string => {
if (lang !== "zh") return fmtUsd(usd);
const v = (Number(usd) || 0) * (rate ?? FALLBACK_RATE);
if (v === 0) return "¥0.00";
if (v < 0.1) return "¥" + v.toFixed(3);
if (v < 1) return "¥" + v.toFixed(2);
return "¥" + v.toFixed(2);
},
[lang, rate],
);
return { money, cnyRate: rate ?? FALLBACK_RATE };
}
+8 -1
View File
@@ -22,16 +22,23 @@ export function useDashboard() {
const [data, setData] = useState<SummaryResult | null>(null);
const [loading, setLoading] = useState(false);
const [error, setError] = useState<string | null>(null);
/** Round-trip timing for the last get_summary call (user-perceived lag). */
const [loadStats, setLoadStats] = useState<{ ms: number; kb: number } | null>(null);
const refresh = useCallback(async (force = false) => {
setLoading(true);
setError(null);
const start = performance.now();
try {
const result = await invoke<SummaryResult>("get_summary", {
range,
refresh: force,
});
setData(result);
setLoadStats({
ms: Math.round(performance.now() - start),
kb: Math.round(JSON.stringify(result).length / 1024),
});
} catch (err) {
const msg = err instanceof Error ? err.message : String(err);
setError(msg);
@@ -53,5 +60,5 @@ export function useDashboard() {
}
}, []);
return { range, changeRange, data, loading, error, refresh };
return { range, changeRange, data, loading, error, refresh, loadStats };
}
+1
View File
@@ -197,6 +197,7 @@ export const enTranslations: Record<TranslationKey, string> = {
scanning: "Scanning…",
refresh: "Refresh",
refreshing: "Refreshing…",
loadStats: "Loaded in {ms} ms · {kb} KB payload",
refreshed: "Refreshed",
cancel: "Cancel",
confirmDeleteTitle: "Delete session forever?",
+1
View File
@@ -194,6 +194,7 @@ export const zhTranslations = {
scanning: "扫描中…",
refresh: "刷新",
refreshing: "刷新中…",
loadStats: "加载 {ms} ms · 数据 {kb} KB",
refreshed: "已刷新",
cancel: "取消",
confirmDeleteTitle: "永久删除会话?",
+478 -71
View File
@@ -17101,7 +17101,9 @@
"output_limit": 8192,
"reasoning": true,
"tool_call": true,
"structured_output": true
"structured_output": true,
"image": true,
"video": true
},
{
"id": "qwen3.6-27b",
@@ -17175,7 +17177,8 @@
"name": "Abliterated Model Large",
"cost": {
"input": 5,
"output": 5
"output": 5,
"cache_read": 0.5
},
"context": 1000000,
"input_limit": 1000000,
@@ -17189,7 +17192,8 @@
"name": "Abliterated Model",
"cost": {
"input": 3,
"output": 3
"output": 3,
"cache_read": 0.3
},
"context": 150000,
"input_limit": 150000,
@@ -18190,7 +18194,9 @@
"output_limit": 65536,
"reasoning": true,
"tool_call": true,
"structured_output": true
"structured_output": true,
"image": true,
"video": true
},
{
"id": "gpt-5.2-chat-latest",
@@ -19796,6 +19802,22 @@
"structured_output": true,
"image": true
},
{
"id": "kimi-k3-fast",
"name": "Kimi K3",
"cost": {
"input": 4.5,
"output": 22.5,
"cache_read": 0.45
},
"context": 1040384,
"output_limit": 131072,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"image": true,
"video": true
},
{
"id": "claude-opus-5",
"name": "Claude Opus 5",
@@ -29065,7 +29087,9 @@
"output_limit": 32768,
"reasoning": true,
"tool_call": true,
"structured_output": true
"structured_output": true,
"image": true,
"video": true
},
{
"id": "Qwen/Qwen3-8B",
@@ -29441,7 +29465,8 @@
"name": "zai-org/GLM-5",
"cost": {
"input": 0.95,
"output": 2.55
"output": 2.55,
"cache_read": 0.2
},
"context": 205000,
"output_limit": 205000,
@@ -29467,6 +29492,7 @@
"cost": {
"input": 1.4,
"output": 4.4,
"cache_read": 0.26,
"cache_write": 0
},
"context": 1049000,
@@ -29481,6 +29507,7 @@
"cost": {
"input": 1.4,
"output": 4.4,
"cache_read": 0.26,
"cache_write": 0
},
"context": 205000,
@@ -29495,6 +29522,7 @@
"cost": {
"input": 1.2,
"output": 4,
"cache_read": 0.24,
"cache_write": 0
},
"context": 200000,
@@ -29824,7 +29852,8 @@
"name": "MiniMaxAI/MiniMax-M2.5",
"cost": {
"input": 0.3,
"output": 1.2
"output": 1.2,
"cache_read": 0.03
},
"context": 197000,
"output_limit": 131000,
@@ -29992,7 +30021,8 @@
"name": "moonshotai/Kimi-K2.5",
"cost": {
"input": 0.45,
"output": 2.25
"output": 2.25,
"cache_read": 0.07
},
"context": 262000,
"output_limit": 262000,
@@ -36790,8 +36820,9 @@
"id": "zai-org-glm-4.7-flash",
"name": "GLM 4.7 Flash",
"cost": {
"input": 0.125,
"output": 0.5
"input": 0.06,
"output": 0.4,
"cache_read": 0.01
},
"context": 128000,
"output_limit": 16384,
@@ -36825,6 +36856,20 @@
"structured_output": true,
"image": true
},
{
"id": "deepseek-v4-flash-0731",
"name": "DeepSeek V4 Flash 0731",
"cost": {
"input": 0.175,
"output": 0.35,
"cache_read": 0.035
},
"context": 1000000,
"output_limit": 32768,
"reasoning": true,
"tool_call": true,
"structured_output": true
},
{
"id": "qwen3-235b-a22b-instruct-2507",
"name": "Qwen 3 235B A22B Instruct 2507",
@@ -37751,7 +37796,8 @@
"name": "GLM-5.1",
"cost": {
"input": 1.4,
"output": 4.4
"output": 4.4,
"cache_read": 0.26
},
"context": 202752,
"output_limit": 131072,
@@ -37822,7 +37868,8 @@
"name": "Qwen3.7 Max",
"cost": {
"input": 1.25,
"output": 3.75
"output": 3.75,
"cache_read": 0.125
},
"context": 1000000,
"output_limit": 500000,
@@ -37844,7 +37891,8 @@
"name": "Qwen3.5 397B A17B",
"cost": {
"input": 0.6,
"output": 3.6
"output": 3.6,
"cache_read": 0.35
},
"context": 262144,
"output_limit": 130000,
@@ -40988,6 +41036,21 @@
"reasoning": true,
"tool_call": true,
"image": true
},
{
"id": "moonshotai/Kimi-K3",
"name": "Kimi K3",
"cost": {
"input": 3,
"output": 15,
"cache_read": 0.3
},
"context": 1048576,
"output_limit": 131072,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"image": true
}
]
},
@@ -41448,7 +41511,9 @@
"name": "MiniMax-M2.1",
"cost": {
"input": 2.1,
"output": 8.4
"output": 8.4,
"cache_read": 2.1,
"cache_write": 8.4
},
"context": 204800,
"output_limit": 131072,
@@ -45670,7 +45735,9 @@
"output_limit": 32000,
"reasoning": true,
"tool_call": true,
"structured_output": true
"structured_output": true,
"image": true,
"video": true
},
{
"id": "nemotron-3-ultra",
@@ -48709,7 +48776,9 @@
"name": "MiniMax-M2.1",
"cost": {
"input": 0.3,
"output": 1.2
"output": 1.2,
"cache_read": 0.03,
"cache_write": 0.375
},
"context": 204800,
"output_limit": 131072,
@@ -49621,6 +49690,355 @@
}
]
},
"tensorx": {
"id": "tensorx",
"name": "TensorX",
"models": [
{
"id": "nvidia/nemotron-3-super-120b-a12b",
"name": "Nemotron 3 Super 120B A12B",
"cost": {
"input": 0.3,
"output": 0.9,
"cache_read": 0.075,
"cache_write": 0.375
},
"context": 262144,
"output_limit": 262144,
"reasoning": true,
"tool_call": true
},
{
"id": "qwen/qwen3-coder-30b-a3b-instruct",
"name": "Qwen3-Coder 30B-A3B Instruct",
"cost": {
"input": 0.06,
"output": 0.25,
"cache_read": 0.015,
"cache_write": 0.075
},
"context": 262000,
"output_limit": 65536,
"tool_call": true
},
{
"id": "qwen/qwen3.5-9b",
"name": "Qwen3.5 9B",
"cost": {
"input": 0.15,
"output": 0.2,
"cache_read": 0.0375,
"cache_write": 0.1875
},
"context": 262144,
"output_limit": 65536,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"image": true,
"video": true
},
{
"id": "qwen/qwen3-vl-235b-a22b-instruct",
"name": "Qwen3 VL 235B-A22B Instruct",
"cost": {
"input": 0.21,
"output": 1.9,
"cache_read": 0.0525,
"cache_write": 0.2625
},
"context": 131000,
"output_limit": 131072,
"tool_call": true,
"image": true
},
{
"id": "qwen/qwen3-235b-a22b-2507",
"name": "Qwen3 235B-A22B-2507",
"cost": {
"input": 0.072,
"output": 0.464,
"cache_read": 0.018,
"cache_write": 0.09
},
"context": 131000,
"output_limit": 262144,
"tool_call": true
},
{
"id": "qwen/qwen3.5-122b-a10b",
"name": "Qwen3.5 122B-A10B",
"cost": {
"input": 0.5,
"output": 3.5,
"cache_read": 0.125,
"cache_write": 0.625
},
"context": 262144,
"output_limit": 262144,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"image": true,
"video": true
},
{
"id": "minimax/minimax-m3",
"name": "MiniMax-M3",
"cost": {
"input": 0.4,
"output": 2,
"cache_read": 0.1
},
"context": 1048576,
"output_limit": 131072,
"reasoning": true,
"tool_call": true,
"image": true,
"video": true
},
{
"id": "minimax/minimax-m2.5",
"name": "MiniMax-M2.5",
"cost": {
"input": 0.3,
"output": 1.2,
"cache_read": 0.075,
"cache_write": 0.375
},
"context": 196608,
"output_limit": 65536,
"reasoning": true,
"tool_call": true
},
{
"id": "deepseek/deepseek-v4-flash",
"name": "DeepSeek V4 Flash",
"cost": {
"input": 0.15,
"output": 0.3,
"cache_read": 0.0375,
"cache_write": 0.1875
},
"context": 1048576,
"output_limit": 384000,
"reasoning": true,
"tool_call": true,
"structured_output": true
},
{
"id": "deepseek/deepseek-v4-pro",
"name": "DeepSeek V4 Pro",
"cost": {
"input": 1.75,
"output": 3.5,
"cache_read": 0.4375,
"cache_write": 2.185
},
"context": 1048576,
"output_limit": 384000,
"reasoning": true,
"tool_call": true,
"structured_output": true
},
{
"id": "deepseek/deepseek-r1-0528",
"name": "DeepSeek R1-0528",
"cost": {
"input": 0.66,
"output": 2.6,
"cache_read": 0.165,
"cache_write": 0.825
},
"context": 164000,
"output_limit": 8192,
"reasoning": true,
"tool_call": true
},
{
"id": "deepseek/deepseek-v3.2",
"name": "DeepSeek V3.2",
"cost": {
"input": 0.3,
"output": 0.5,
"cache_read": 0.075,
"cache_write": 0.375
},
"context": 163840,
"output_limit": 163840,
"reasoning": true,
"tool_call": true
},
{
"id": "deepseek/deepseek-chat-v3.1",
"name": "DeepSeek Chat V3.1",
"cost": {
"input": 0.2,
"output": 0.8,
"cache_read": 0.05,
"cache_write": 0.25
},
"context": 164000,
"output_limit": 163840,
"reasoning": true,
"tool_call": true
},
{
"id": "z-ai/glm-5",
"name": "GLM-5",
"cost": {
"input": 1,
"output": 3.2,
"cache_read": 0.25,
"cache_write": 1.25
},
"context": 202752,
"output_limit": 202752,
"reasoning": true,
"tool_call": true
},
{
"id": "z-ai/glm-5.1",
"name": "GLM-5.1",
"cost": {
"input": 1.4,
"output": 4.4,
"cache_read": 0.35,
"cache_write": 1.75
},
"context": 202752,
"output_limit": 202752,
"reasoning": true,
"tool_call": true,
"structured_output": true
},
{
"id": "z-ai/glm-5.2",
"name": "GLM-5.2",
"cost": {
"input": 1.5,
"output": 4.5,
"cache_read": 0.375
},
"context": 1048576,
"output_limit": 131072,
"reasoning": true,
"tool_call": true,
"structured_output": true
},
{
"id": "z-ai/glm-4.7",
"name": "GLM-4.7",
"cost": {
"input": 0.6,
"output": 2.2,
"cache_read": 0.15,
"cache_write": 0.75
},
"context": 200000,
"output_limit": 200000,
"reasoning": true,
"tool_call": true,
"image": true
},
{
"id": "z-ai/glm-5-turbo",
"name": "GLM-5-Turbo",
"cost": {
"input": 1.2,
"output": 4,
"cache_read": 0.3,
"cache_write": 1.5
},
"context": 202752,
"output_limit": 131072,
"reasoning": true,
"tool_call": true,
"structured_output": true
},
{
"id": "z-ai/glm-5v-turbo",
"name": "GLM-5V-Turbo",
"cost": {
"input": 1.2,
"output": 4,
"cache_read": 0.3,
"cache_write": 1.5
},
"context": 202752,
"output_limit": 131072,
"reasoning": true,
"tool_call": true,
"image": true,
"video": true
},
{
"id": "moonshotai/kimi-k2.5",
"name": "Kimi K2.5",
"cost": {
"input": 0.5,
"output": 2.8,
"cache_read": 0.125,
"cache_write": 0.625
},
"context": 262144,
"output_limit": 262144,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"image": true,
"video": true
},
{
"id": "moonshotai/kimi-k2.6",
"name": "Kimi K2.6",
"cost": {
"input": 1,
"output": 4,
"cache_read": 0.25,
"cache_write": 1.25
},
"context": 262144,
"output_limit": 262144,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"image": true,
"video": true
},
{
"id": "moonshotai/kimi-k2.7-code",
"name": "Kimi K2.7 Code",
"cost": {
"input": 1.25,
"output": 4.5,
"cache_read": 0.3125
},
"context": 262144,
"output_limit": 262144,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"image": true,
"video": true
},
{
"id": "openai/gpt-oss-120b",
"name": "GPT OSS 120B",
"cost": {
"input": 0.04,
"output": 0.2,
"cache_read": 0.01,
"cache_write": 0.05
},
"context": 131072,
"output_limit": 32768,
"reasoning": true,
"tool_call": true,
"structured_output": true
}
]
},
"llama": {
"id": "llama",
"name": "Llama",
@@ -58117,7 +58535,8 @@
"cache_read": 0.03
},
"context": 32768,
"output_limit": 65536
"output_limit": 65536,
"image": true
},
{
"id": "google/imagen-4.0-generate-001",
@@ -58133,7 +58552,8 @@
"cache_read": 0.2
},
"context": 65536,
"output_limit": 32768
"output_limit": 32768,
"image": true
},
{
"id": "google/gemini-3.1-pro-preview",
@@ -58150,6 +58570,10 @@
"structured_output": true,
"image": true
},
{
"id": "google/veo-3.1-lite-generate-001",
"name": "Veo 3.1 Lite Generate"
},
{
"id": "google/gemini-2.5-flash-lite",
"name": "Gemini 2.5 Flash Lite",
@@ -58868,7 +59292,8 @@
},
"context": 128000,
"output_limit": 128000,
"tool_call": true
"tool_call": true,
"image": true
},
{
"id": "mistral/mistral-small",
@@ -59198,6 +59623,19 @@
"tool_call": true,
"structured_output": true
},
{
"id": "deepseek/deepseek-v4-flash-0731",
"name": "DeepSeek V4 Flash 0731",
"cost": {
"input": 0.13,
"output": 0.26,
"cache_read": 0.028
},
"context": 1000000,
"output_limit": 384000,
"reasoning": true,
"tool_call": true
},
{
"id": "deepseek/deepseek-v3",
"name": "DeepSeek V3 0324",
@@ -59714,7 +60152,8 @@
"context": 256000,
"output_limit": 80000,
"reasoning": true,
"tool_call": true
"tool_call": true,
"image": true
},
{
"id": "kwaipilot/kat-coder-air-v2.5",
@@ -59727,7 +60166,8 @@
"context": 256000,
"output_limit": 80000,
"reasoning": true,
"tool_call": true
"tool_call": true,
"image": true
},
{
"id": "xiaomi/mimo-v2.5",
@@ -60018,7 +60458,8 @@
"name": "Sonar Reasoning Pro",
"context": 127000,
"output_limit": 8000,
"reasoning": true
"reasoning": true,
"image": true
},
{
"id": "moonshotai/kimi-k2.5",
@@ -61102,7 +61543,8 @@
"context": 262114,
"output_limit": 262114,
"reasoning": true,
"tool_call": true
"tool_call": true,
"image": true
},
{
"id": "stepfun/step-3.7-flash",
@@ -68833,7 +69275,9 @@
"name": "MiniMax-M2.1",
"cost": {
"input": 0,
"output": 0
"output": 0,
"cache_read": 0,
"cache_write": 0
},
"context": 204800,
"output_limit": 131072,
@@ -68910,6 +69354,7 @@
"cost": {
"input": 1.4,
"output": 4.4,
"cache_read": 0.26,
"cache_write": 0
},
"context": 1049000,
@@ -68973,6 +69418,7 @@
"cost": {
"input": 1.4,
"output": 4.4,
"cache_read": 0.26,
"cache_write": 0
},
"context": 205000,
@@ -69064,7 +69510,8 @@
"name": "Pro/moonshotai/Kimi-K2.5",
"cost": {
"input": 0.45,
"output": 2.25
"output": 2.25,
"cache_read": 0.07
},
"context": 262000,
"output_limit": 262000,
@@ -72114,20 +72561,6 @@
"structured_output": true,
"image": true
},
{
"id": "zai-org/GLM-5-TEE",
"name": "GLM 5 TEE",
"cost": {
"input": 0.95,
"output": 2.55,
"cache_read": 0.475
},
"context": 202752,
"output_limit": 65535,
"reasoning": true,
"tool_call": true,
"structured_output": true
},
{
"id": "zai-org/GLM-5.1-TEE",
"name": "GLM 5.1 TEE",
@@ -72225,20 +72658,6 @@
"structured_output": true,
"image": true
},
{
"id": "MiniMaxAI/MiniMax-M2.5-TEE",
"name": "MiniMax M2.5 TEE",
"cost": {
"input": 0.15,
"output": 1.2,
"cache_read": 0.075
},
"context": 196608,
"output_limit": 65536,
"reasoning": true,
"tool_call": true,
"structured_output": true
},
{
"id": "deepseek-ai/DeepSeek-V3.2-TEE",
"name": "DeepSeek V3.2 TEE",
@@ -72269,22 +72688,6 @@
"image": true,
"video": true
},
{
"id": "moonshotai/Kimi-K2.5-TEE",
"name": "Kimi K2.5 TEE",
"cost": {
"input": 0.44,
"output": 2,
"cache_read": 0.22
},
"context": 262144,
"output_limit": 65535,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"image": true,
"video": true
},
{
"id": "moonshotai/Kimi-K3-TEE",
"name": "Kimi K3 TEE",
@@ -77090,7 +77493,9 @@
"name": "MiniMax-M2.1",
"cost": {
"input": 0.3,
"output": 1.2
"output": 1.2,
"cache_read": 0.03,
"cache_write": 0.375
},
"context": 204800,
"output_limit": 131072,
@@ -77719,7 +78124,9 @@
"name": "MiniMax-M2.1",
"cost": {
"input": 0,
"output": 0
"output": 0,
"cache_read": 0,
"cache_write": 0
},
"context": 204800,
"output_limit": 131072,
+407 -55
View File
@@ -13610,6 +13610,8 @@
"reasoning": true,
"tool_call": true,
"structured_output": true,
"image": true,
"video": true,
"cost": {
"input": 0,
"output": 0
@@ -13674,7 +13676,8 @@
"structured_output": true,
"cost": {
"input": 5,
"output": 5
"output": 5,
"cache_read": 0.5
}
},
"abliteration-ai/abliterated-model": {
@@ -13685,7 +13688,8 @@
"image": true,
"cost": {
"input": 3,
"output": 3
"output": 3,
"cache_read": 0.3
}
},
"alibaba-coding-plan-cn/qwen3.7-plus": {
@@ -14520,6 +14524,8 @@
"reasoning": true,
"tool_call": true,
"structured_output": true,
"image": true,
"video": true,
"cost": {
"input": 0.1,
"output": 0.15
@@ -15883,6 +15889,20 @@
"cache_read": 0.2
}
},
"llmgateway/kimi-k3-fast": {
"name": "Kimi K3",
"context": 1040384,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"image": true,
"video": true,
"cost": {
"input": 4.5,
"output": 22.5,
"cache_read": 0.45
}
},
"llmgateway/claude-opus-5": {
"name": "Claude Opus 5",
"context": 1000000,
@@ -23525,6 +23545,8 @@
"reasoning": true,
"tool_call": true,
"structured_output": true,
"image": true,
"video": true,
"cost": {
"input": 0.3,
"output": 0.3,
@@ -23853,7 +23875,8 @@
"structured_output": true,
"cost": {
"input": 0.95,
"output": 2.55
"output": 2.55,
"cache_read": 0.2
}
},
"siliconflow/zai-org/GLM-4.5-Air": {
@@ -23875,6 +23898,7 @@
"cost": {
"input": 1.4,
"output": 4.4,
"cache_read": 0.26,
"cache_write": 0
}
},
@@ -23887,6 +23911,7 @@
"cost": {
"input": 1.4,
"output": 4.4,
"cache_read": 0.26,
"cache_write": 0
}
},
@@ -23899,6 +23924,7 @@
"cost": {
"input": 1.2,
"output": 4,
"cache_read": 0.24,
"cache_write": 0
}
},
@@ -24174,7 +24200,8 @@
"tool_call": true,
"cost": {
"input": 0.3,
"output": 1.2
"output": 1.2,
"cache_read": 0.03
}
},
"siliconflow/inclusionAI/Ling-flash-2.0": {
@@ -24319,7 +24346,8 @@
"image": true,
"cost": {
"input": 0.45,
"output": 2.25
"output": 2.25,
"cache_read": 0.07
}
},
"siliconflow/openai/gpt-oss-20b": {
@@ -29988,8 +30016,9 @@
"tool_call": true,
"structured_output": true,
"cost": {
"input": 0.125,
"output": 0.5
"input": 0.06,
"output": 0.4,
"cache_read": 0.01
}
},
"venice/llama-3.2-3b": {
@@ -30013,6 +30042,18 @@
"output": 225
}
},
"venice/deepseek-v4-flash-0731": {
"name": "DeepSeek V4 Flash 0731",
"context": 1000000,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"cost": {
"input": 0.175,
"output": 0.35,
"cache_read": 0.035
}
},
"venice/qwen3-235b-a22b-instruct-2507": {
"name": "Qwen 3 235B A22B Instruct 2507",
"context": 128000,
@@ -30792,7 +30833,8 @@
"structured_output": true,
"cost": {
"input": 1.4,
"output": 4.4
"output": 4.4,
"cache_read": 0.26
}
},
"togetherai/pearl-ai/gemma-4-31b-it": {
@@ -30849,7 +30891,8 @@
"tool_call": true,
"cost": {
"input": 1.25,
"output": 3.75
"output": 3.75,
"cache_read": 0.125
}
},
"togetherai/Qwen/Qwen3-235B-A22B-Instruct-2507-tput": {
@@ -30869,7 +30912,8 @@
"image": true,
"cost": {
"input": 0.6,
"output": 3.6
"output": 3.6,
"cache_read": 0.35
}
},
"togetherai/Qwen/Qwen3.6-Plus": {
@@ -33439,6 +33483,19 @@
"cache_read": 0.27
}
},
"modal/moonshotai/Kimi-K3": {
"name": "Kimi K3",
"context": 1048576,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"image": true,
"cost": {
"input": 3,
"output": 15,
"cache_read": 0.3
}
},
"qihang-ai/gemini-2.5-flash": {
"name": "Gemini 2.5 Flash",
"context": 1048576,
@@ -33814,7 +33871,9 @@
"tool_call": true,
"cost": {
"input": 2.1,
"output": 8.4
"output": 8.4,
"cache_read": 2.1,
"cache_write": 8.4
}
},
"moark/GLM-4.7": {
@@ -37298,6 +37357,8 @@
"reasoning": true,
"tool_call": true,
"structured_output": true,
"image": true,
"video": true,
"cost": {
"input": 0.16,
"output": 0.48
@@ -39859,7 +39920,9 @@
"tool_call": true,
"cost": {
"input": 0.3,
"output": 1.2
"output": 1.2,
"cache_read": 0.03,
"cache_write": 0.375
}
},
"minimax/MiniMax-M2.5": {
@@ -40611,6 +40674,303 @@
"cache_read": 0.11
}
},
"tensorx/nvidia/nemotron-3-super-120b-a12b": {
"name": "Nemotron 3 Super 120B A12B",
"context": 262144,
"reasoning": true,
"tool_call": true,
"cost": {
"input": 0.3,
"output": 0.9,
"cache_read": 0.075,
"cache_write": 0.375
}
},
"tensorx/qwen/qwen3-coder-30b-a3b-instruct": {
"name": "Qwen3-Coder 30B-A3B Instruct",
"context": 262000,
"tool_call": true,
"cost": {
"input": 0.06,
"output": 0.25,
"cache_read": 0.015,
"cache_write": 0.075
}
},
"tensorx/qwen/qwen3.5-9b": {
"name": "Qwen3.5 9B",
"context": 262144,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"image": true,
"video": true,
"cost": {
"input": 0.15,
"output": 0.2,
"cache_read": 0.0375,
"cache_write": 0.1875
}
},
"tensorx/qwen/qwen3-vl-235b-a22b-instruct": {
"name": "Qwen3 VL 235B-A22B Instruct",
"context": 131000,
"tool_call": true,
"image": true,
"cost": {
"input": 0.21,
"output": 1.9,
"cache_read": 0.0525,
"cache_write": 0.2625
}
},
"tensorx/qwen/qwen3-235b-a22b-2507": {
"name": "Qwen3 235B-A22B-2507",
"context": 131000,
"tool_call": true,
"cost": {
"input": 0.072,
"output": 0.464,
"cache_read": 0.018,
"cache_write": 0.09
}
},
"tensorx/qwen/qwen3.5-122b-a10b": {
"name": "Qwen3.5 122B-A10B",
"context": 262144,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"image": true,
"video": true,
"cost": {
"input": 0.5,
"output": 3.5,
"cache_read": 0.125,
"cache_write": 0.625
}
},
"tensorx/minimax/minimax-m3": {
"name": "MiniMax-M3",
"context": 1048576,
"reasoning": true,
"tool_call": true,
"image": true,
"video": true,
"cost": {
"input": 0.4,
"output": 2,
"cache_read": 0.1
}
},
"tensorx/minimax/minimax-m2.5": {
"name": "MiniMax-M2.5",
"context": 196608,
"reasoning": true,
"tool_call": true,
"cost": {
"input": 0.3,
"output": 1.2,
"cache_read": 0.075,
"cache_write": 0.375
}
},
"tensorx/deepseek/deepseek-v4-flash": {
"name": "DeepSeek V4 Flash",
"context": 1048576,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"cost": {
"input": 0.15,
"output": 0.3,
"cache_read": 0.0375,
"cache_write": 0.1875
}
},
"tensorx/deepseek/deepseek-v4-pro": {
"name": "DeepSeek V4 Pro",
"context": 1048576,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"cost": {
"input": 1.75,
"output": 3.5,
"cache_read": 0.4375,
"cache_write": 2.185
}
},
"tensorx/deepseek/deepseek-r1-0528": {
"name": "DeepSeek R1-0528",
"context": 164000,
"reasoning": true,
"tool_call": true,
"cost": {
"input": 0.66,
"output": 2.6,
"cache_read": 0.165,
"cache_write": 0.825
}
},
"tensorx/deepseek/deepseek-v3.2": {
"name": "DeepSeek V3.2",
"context": 163840,
"reasoning": true,
"tool_call": true,
"cost": {
"input": 0.3,
"output": 0.5,
"cache_read": 0.075,
"cache_write": 0.375
}
},
"tensorx/deepseek/deepseek-chat-v3.1": {
"name": "DeepSeek Chat V3.1",
"context": 164000,
"reasoning": true,
"tool_call": true,
"cost": {
"input": 0.2,
"output": 0.8,
"cache_read": 0.05,
"cache_write": 0.25
}
},
"tensorx/z-ai/glm-5": {
"name": "GLM-5",
"context": 202752,
"reasoning": true,
"tool_call": true,
"cost": {
"input": 1,
"output": 3.2,
"cache_read": 0.25,
"cache_write": 1.25
}
},
"tensorx/z-ai/glm-5.1": {
"name": "GLM-5.1",
"context": 202752,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"cost": {
"input": 1.4,
"output": 4.4,
"cache_read": 0.35,
"cache_write": 1.75
}
},
"tensorx/z-ai/glm-5.2": {
"name": "GLM-5.2",
"context": 1048576,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"cost": {
"input": 1.5,
"output": 4.5,
"cache_read": 0.375
}
},
"tensorx/z-ai/glm-4.7": {
"name": "GLM-4.7",
"context": 200000,
"reasoning": true,
"tool_call": true,
"image": true,
"cost": {
"input": 0.6,
"output": 2.2,
"cache_read": 0.15,
"cache_write": 0.75
}
},
"tensorx/z-ai/glm-5-turbo": {
"name": "GLM-5-Turbo",
"context": 202752,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"cost": {
"input": 1.2,
"output": 4,
"cache_read": 0.3,
"cache_write": 1.5
}
},
"tensorx/z-ai/glm-5v-turbo": {
"name": "GLM-5V-Turbo",
"context": 202752,
"reasoning": true,
"tool_call": true,
"image": true,
"video": true,
"cost": {
"input": 1.2,
"output": 4,
"cache_read": 0.3,
"cache_write": 1.5
}
},
"tensorx/moonshotai/kimi-k2.5": {
"name": "Kimi K2.5",
"context": 262144,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"image": true,
"video": true,
"cost": {
"input": 0.5,
"output": 2.8,
"cache_read": 0.125,
"cache_write": 0.625
}
},
"tensorx/moonshotai/kimi-k2.6": {
"name": "Kimi K2.6",
"context": 262144,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"image": true,
"video": true,
"cost": {
"input": 1,
"output": 4,
"cache_read": 0.25,
"cache_write": 1.25
}
},
"tensorx/moonshotai/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": 1.25,
"output": 4.5,
"cache_read": 0.3125
}
},
"tensorx/openai/gpt-oss-120b": {
"name": "GPT OSS 120B",
"context": 131072,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"cost": {
"input": 0.04,
"output": 0.2,
"cache_read": 0.01,
"cache_write": 0.05
}
},
"llama/cerebras-llama-4-maverick-17b-128e-instruct": {
"name": "Cerebras-Llama-4-Maverick-17B-128E-Instruct",
"context": 128000,
@@ -47689,6 +48049,7 @@
"vercel/google/gemini-2.5-flash-image": {
"name": "Nano Banana (Gemini 2.5 Flash Image)",
"context": 32768,
"image": true,
"cost": {
"input": 0.3,
"output": 2.5,
@@ -47702,6 +48063,7 @@
"vercel/google/gemini-3-pro-image": {
"name": "Nano Banana Pro",
"context": 65536,
"image": true,
"cost": {
"input": 2,
"output": 12,
@@ -47721,6 +48083,9 @@
"cache_read": 0.2
}
},
"vercel/google/veo-3.1-lite-generate-001": {
"name": "Veo 3.1 Lite Generate"
},
"vercel/google/gemini-2.5-flash-lite": {
"name": "Gemini 2.5 Flash Lite",
"context": 1048576,
@@ -48298,6 +48663,7 @@
"name": "Mistral Nemo",
"context": 128000,
"tool_call": true,
"image": true,
"cost": {
"input": 0.15,
"output": 0.15
@@ -48578,6 +48944,17 @@
"cache_read": 0.0036
}
},
"vercel/deepseek/deepseek-v4-flash-0731": {
"name": "DeepSeek V4 Flash 0731",
"context": 1000000,
"reasoning": true,
"tool_call": true,
"cost": {
"input": 0.13,
"output": 0.26,
"cache_read": 0.028
}
},
"vercel/deepseek/deepseek-v3": {
"name": "DeepSeek V3 0324",
"context": 163840,
@@ -49002,6 +49379,7 @@
"context": 256000,
"reasoning": true,
"tool_call": true,
"image": true,
"cost": {
"input": 0.74,
"output": 2.96,
@@ -49013,6 +49391,7 @@
"context": 256000,
"reasoning": true,
"tool_call": true,
"image": true,
"cost": {
"input": 0.15,
"output": 0.6,
@@ -49266,7 +49645,8 @@
"vercel/perplexity/sonar-reasoning-pro": {
"name": "Sonar Reasoning Pro",
"context": 127000,
"reasoning": true
"reasoning": true,
"image": true
},
"vercel/moonshotai/kimi-k2.5": {
"name": "Kimi K2.5",
@@ -50157,6 +50537,7 @@
"context": 262114,
"reasoning": true,
"tool_call": true,
"image": true,
"cost": {
"input": 0.09,
"output": 0.3,
@@ -56667,7 +57048,9 @@
"tool_call": true,
"cost": {
"input": 0,
"output": 0
"output": 0,
"cache_read": 0,
"cache_write": 0
}
},
"minimax-coding-plan/MiniMax-M2.5": {
@@ -56729,6 +57112,7 @@
"cost": {
"input": 1.4,
"output": 4.4,
"cache_read": 0.26,
"cache_write": 0
}
},
@@ -56782,6 +57166,7 @@
"cost": {
"input": 1.4,
"output": 4.4,
"cache_read": 0.26,
"cache_write": 0
}
},
@@ -56860,7 +57245,8 @@
"image": true,
"cost": {
"input": 0.45,
"output": 2.25
"output": 2.25,
"cache_read": 0.07
}
},
"siliconflow-cn/Qwen/Qwen3.5-27B": {
@@ -59386,18 +59772,6 @@
"cache_read": 0.06
}
},
"chutes/zai-org/GLM-5-TEE": {
"name": "GLM 5 TEE",
"context": 202752,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"cost": {
"input": 0.95,
"output": 2.55,
"cache_read": 0.475
}
},
"chutes/zai-org/GLM-5.1-TEE": {
"name": "GLM 5.1 TEE",
"context": 202752,
@@ -59481,18 +59855,6 @@
"cache_read": 0.225
}
},
"chutes/MiniMaxAI/MiniMax-M2.5-TEE": {
"name": "MiniMax M2.5 TEE",
"context": 196608,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"cost": {
"input": 0.15,
"output": 1.2,
"cache_read": 0.075
}
},
"chutes/deepseek-ai/DeepSeek-V3.2-TEE": {
"name": "DeepSeek V3.2 TEE",
"context": 131072,
@@ -59519,20 +59881,6 @@
"cache_read": 0.33
}
},
"chutes/moonshotai/Kimi-K2.5-TEE": {
"name": "Kimi K2.5 TEE",
"context": 262144,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"image": true,
"video": true,
"cost": {
"input": 0.44,
"output": 2,
"cache_read": 0.22
}
},
"chutes/moonshotai/Kimi-K3-TEE": {
"name": "Kimi K3 TEE",
"context": 1048576,
@@ -63413,7 +63761,9 @@
"tool_call": true,
"cost": {
"input": 0.3,
"output": 1.2
"output": 1.2,
"cache_read": 0.03,
"cache_write": 0.375
}
},
"minimax-cn/MiniMax-M2.5": {
@@ -63930,7 +64280,9 @@
"tool_call": true,
"cost": {
"input": 0,
"output": 0
"output": 0,
"cache_read": 0,
"cache_write": 0
}
},
"minimax-cn-coding-plan/MiniMax-M2.5": {
+2 -2
View File
@@ -13,7 +13,7 @@
/>
<meta
name="keywords"
content="KimiSwitch, KimiCodeSwitch, SwitchKimi, Kimi Code Switch, Kimi 切换, LLM 供应商管理, AI 供应商切换, 多 LLM 管理, Kimi 用量监控, 智谱 GLM, MiniMax, DeepSeek, OpenRouter, 基元律动, 用量查询, 账单监控, Token 套餐, Claude, GPT, Windows LLM 桌面工具"
content="Kimi Switch, KimiSwitch, KimiCode Switch, KimiCodeSwitch, SwitchKimi, Kimi Code Switch, Kimi 切换, LLM 供应商管理, AI 供应商切换, 多 LLM 管理, Kimi 用量监控, 智谱 GLM, MiniMax, DeepSeek, OpenRouter, 基元律动, 用量查询, 账单监控, Token 套餐, Claude, GPT, Windows LLM 桌面工具"
/>
<!-- Open Graph -->
@@ -46,7 +46,7 @@
{
"@type": "SoftwareApplication",
"name": "Kimi Switch",
"alternateName": ["KimiSwitch", "KimiCodeSwitch"],
"alternateName": ["KimiSwitch", "KimiCodeSwitch", "Kimi Switch", "KimiCode Switch"],
"url": "https://billowliu2.github.io/KimiSwitch/",
"applicationCategory": "DeveloperApplication",
"operatingSystem": "Windows 10, Windows 11",
-1
View File
@@ -1 +0,0 @@
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" fill="#0F62FE"><path d="M12 2L4 6v6c0 5 3.5 8.5 8 10 4.5-1.5 8-5 8-10V6l-8-4zm0 4l4 2v4c0 3-1.5 5-4 6-2.5-1-4-3-4-6V8l4-2z"/></svg>

Before

Width:  |  Height:  |  Size: 192 B

+1 -1
View File
@@ -5,7 +5,7 @@ import { asset } from "../lib/asset";
/** Map recommendLink.name → logo file in public/logos (only when we have one). */
const logoFor: Record<string, string> = {
"Kimi": "logos/kimi.svg",
"智谱 GLM": "logos/glm.svg",
"智谱 GLM": "logos/zhipu.svg",
"DeepSeek": "logos/deepseek.svg",
"OpenCodeGo": "logos/opencode.svg",
"MiniMax": "logos/minimax.svg",
+24 -14
View File
@@ -16,10 +16,10 @@ const zh = {
performance: "性能",
changelog: "更新日志",
download: "下载",
downloadBtn: "下载 v0.6.8",
downloadBtn: "下载 v0.6.9",
},
hero: {
badge: "开源 MIT · Windows 10 / 11",
badge: "v0.6.9 · 开源 MIT · Windows / macOS / Linux",
titleBefore: "统一管理你的",
titleAccent: "AI 供应商",
titleAfter: "",
@@ -140,6 +140,15 @@ const zh = {
syncedNote: "数据已同步 GitHub Releases",
fallbackNote: "内置版本记录",
entries: [
{
version: "v0.6.9",
date: "2026-08-01",
items: [
"最近请求新增缓存命中率列,每次请求命中一目了然",
"中文模式费用按最新汇率换算人民币(¥)显示,英文模式保持美元",
"仪表盘性能再优化:价格解析记忆化缓存,扫描从秒级降到百毫秒级;右上角新增加载耗时/数据量跟踪",
],
},
{
version: "v0.6.8",
date: "2026-08-01",
@@ -150,14 +159,6 @@ const zh = {
"官网更新:Kimi 风格重设计、中英文切换、更新日志同步 GitHub Releases、三平台下载",
],
},
{
version: "v0.6.7",
date: "2026-08-01",
items: [
"应用内置 Kimi 设备授权登录(等同 kimi login),浏览器授权即用,过期自动续期",
"外链打开统一走 Rust 命令,修复部分链接无法跳转",
],
},
{
version: "v0.6.6",
date: "2026-08-01",
@@ -244,7 +245,7 @@ const zh = {
},
download: {
title: "下载 Kimi Switch",
subtitle: "当前版本 v0.6.8 · Windows / macOS / Linux 三平台已发布",
subtitle: "当前版本 v0.6.9 · Windows / macOS / Linux 三平台已发布",
autoUpdate: "应用内置自动检测更新,新版本发布后在设置页一键升级。",
ready: "已发布",
wip: "开发中",
@@ -312,10 +313,10 @@ const en: Dict = {
performance: "Performance",
changelog: "Changelog",
download: "Download",
downloadBtn: "Download v0.6.8",
downloadBtn: "Download v0.6.9",
},
hero: {
badge: "Open source MIT · Windows 10 / 11",
badge: "v0.6.9 · Open source MIT · Windows / macOS / Linux",
titleBefore: "One app for all your ",
titleAccent: "AI providers",
titleAfter: "",
@@ -436,6 +437,15 @@ const en: Dict = {
syncedNote: "Synced from GitHub Releases",
fallbackNote: "Built-in release notes",
entries: [
{
version: "v0.6.9",
date: "2026-08-01",
items: [
"Recent requests gain a cache-hit-rate column, per request at a glance",
"Chinese UI now shows costs in CNY (latest exchange rate); English keeps USD",
"Dashboard speedup: memoized price resolution drops the scan from seconds to milliseconds; load time / payload tracking in the top-right corner",
],
},
{
version: "v0.6.8",
date: "2026-08-01",
@@ -540,7 +550,7 @@ const en: Dict = {
},
download: {
title: "Download Kimi Switch",
subtitle: "Current version v0.6.8 · Windows, macOS and Linux now released",
subtitle: "Current version v0.6.9 · Windows, macOS and Linux now released",
autoUpdate: "Built-in update detection: upgrade in one click from Settings when a new version ships.",
ready: "Available",
wip: "In development",
+12 -7
View File
@@ -10,9 +10,14 @@ interface ChangelogEntry {
const API_URL =
"https://api.github.com/repos/billowliu2/KimiSwitch/releases?per_page=20";
const CACHE_KEY = "kimi-switch-changelog";
const CACHE_TTL = 60 * 60 * 1000; // 1 hour
/** Cache key is versioned by the newest embedded release so redeploys
* invalidate stale caches in the browser immediately. */
function cacheKey(embedded: ChangelogEntry[]) {
return `kimi-switch-changelog-${embedded[0]?.version ?? "v1"}`;
}
/** Parse a GitHub release body into bullet items. */
function parseBody(body: string): string[] {
return body
@@ -36,9 +41,9 @@ async function fetchReleases(): Promise<ChangelogEntry[]> {
}));
}
function readCache(): ChangelogEntry[] | null {
function readCache(embedded: ChangelogEntry[]): ChangelogEntry[] | null {
try {
const raw = localStorage.getItem(CACHE_KEY);
const raw = localStorage.getItem(cacheKey(embedded));
if (!raw) return null;
const { ts, data } = JSON.parse(raw) as { ts: number; data: ChangelogEntry[] };
if (Date.now() - ts > CACHE_TTL) return null;
@@ -48,10 +53,10 @@ function readCache(): ChangelogEntry[] | null {
}
}
function writeCache(data: ChangelogEntry[]) {
function writeCache(data: ChangelogEntry[], embedded: ChangelogEntry[]) {
try {
localStorage.setItem(
CACHE_KEY,
cacheKey(embedded),
JSON.stringify({ ts: Date.now(), data }),
);
} catch {
@@ -67,7 +72,7 @@ export default function Changelog() {
useEffect(() => {
let cancelled = false;
const cached = readCache();
const cached = readCache(embedded);
if (cached) {
setRemote(cached);
setSynced(true);
@@ -78,7 +83,7 @@ export default function Changelog() {
if (cancelled) return;
setRemote(data);
setSynced(true);
writeCache(data);
writeCache(data, embedded);
})
.catch(() => {
/* 网络不通时使用内置列表兜底 */
+7 -7
View File
@@ -8,25 +8,25 @@ const icons: Record<string, Icon> = {
linux: LinuxLogo,
};
const VERSION = "0.6.8";
const VERSION = "0.6.9";
const GITHUB = "https://github.com/billowliu2/KimiSwitch";
const MIRROR_RELEASES = "https://git.codingplan.site/admin/KimiCodeSwitch/releases";
const dl = (file: string) => `${GITHUB}/releases/download/v${VERSION}/${file}`;
/** Per-platform download assets for the current release (names match the CI
* release workflow, e.g. Kimi.Switch_0.6.8_x64_en-US.msi). */
* release workflow, e.g. Kimi.Switch_0.6.9_x64_en-US.msi). */
const assets: Record<string, { label: string; href: string }[]> = {
windows: [
{ label: "MSI", href: dl("Kimi.Switch_0.6.8_x64_en-US.msi") },
{ label: "MSI", href: dl("Kimi.Switch_0.6.9_x64_en-US.msi") },
{ label: "镜像", href: MIRROR_RELEASES },
],
macos: [
{ label: "Apple Silicon (.dmg)", href: dl("Kimi.Switch_0.6.8_aarch64.dmg") },
{ label: "Apple Silicon (.dmg)", href: dl("Kimi.Switch_0.6.9_aarch64.dmg") },
],
linux: [
{ label: ".deb", href: dl("Kimi.Switch_0.6.8_amd64.deb") },
{ label: ".AppImage", href: dl("Kimi.Switch_0.6.8_amd64.AppImage") },
{ label: ".rpm", href: dl("Kimi.Switch-0.6.8-1.x86_64.rpm") },
{ label: ".deb", href: dl("Kimi.Switch_0.6.9_amd64.deb") },
{ label: ".AppImage", href: dl("Kimi.Switch_0.6.9_amd64.AppImage") },
{ label: ".rpm", href: dl("Kimi.Switch-0.6.9-1.x86_64.rpm") },
],
};