Live · 25 models · real API tests since August 2025

Models change overnight. Your router should know.

AI Stupid Level benchmarks 25 frontier models around the clock and routes every request to whichever one is measurably best right now — for code, reasoning, tool use, speed or cost. One OpenAI-compatible endpoint. Your own provider keys. Zero markup on tokens.

Free account: every ranking, a 3-model watchlist and 1,000 routed requests a month. No card.

0%
markup on tokens. Providers bill you directly, at their own list price.
14
auto-* routing modes, from auto-coding to auto-cheapest.
10 min
between health checks on every provider the router can pick.
Smart Router · live routing decisions
Example requests · live router picks
Incoming requests
  1. auto-codingstream
    Fix the race condition in checkout.ts
    → GPT-5.6 Luna · 200
Model
auto-coding
Strategy
best_coding
Ranked on
Coding suite: real repository bug fixes, every 4 hours
Passed over
none
Routed to
GPT-5.6 Luna
Ranking for this requestCoding score
1GPT-5.6 LunaOpenAIrouted97.2
2DeepSeek V4.1 FlashDeepSeekfallback94.8
3Claude Opus 5.5Anthropicfallback97.3
4Claude Opus 4.7Anthropic93.2
5GPT-5.5OpenAI93.2
6GPT-5.6 SolOpenAI93.2
7GPT-5.6 TerraOpenAI93.2

Live · 25 models · real API tests since August 2025

Is your AI worth what you’re paying? And is it still as good as last month?

AI Stupid Level has tested AI models on a fixed schedule since August 2025: every model on the same tasks, through each provider’s own API. Not votes, measurements. See which models get the job done, what a correct result really costs, and when a model changes. Our Smart Router puts it to work, sending every request to the model that is measurably best right now.

Building on AI? We benchmark the models on your own work, and keep it running. Free account: every ranking, a 3-model watchlist and 1,000 routed requests a month. No card.

What a correct fix really costsCoding · last 30 days
Claude Fable 5.1Anthropic$39.53
77% of attempts passedper 1,000 correct fixes
GPT-6 LunaOpenAI$0.34
85% of attempts passedper 1,000 correct fixes

116× less per correct fix, and GPT-6 Luna passed more often.

Same 7 bug-fix tasks for both, 29 Sep – 29 Oct, every attempt at the provider’s list price. Picked by rule: the model whose correct fixes cost the most, next to the cheapest that passed at least as often.

Measured and routed across 6 providers

  • OpenAI
  • Anthropic
  • Google
  • DeepSeek
  • Moonshot AI
  • Z.ai

Works with the tools you build on

  • OpenClaw
  • DeepSeek Harness
  • Hermes Agent
  • OpenCode
  • Open WebUI
  • Langflow
  • LangChain
  • n8n
  • MCP
  • Dify
  • Pi
  • LobeHub
  • browser-use
  • Cline
  • LiteLLM
  • Fabric
  • oh-my-pi
  • Mastra
  • Kilo Code
  • Vercel AI SDK
  • CrewAI
  • RAGFlow
  • AnythingLLM
  • Open Interpreter
  • Cherry Studio
  • LibreChat
  • Haystack
  • Agent Zero
  • promptfoo
  • Crush
  • opencodex
  • Hermes Desktop
  • DeepChat
How to connect each one
14months of real API tests, since August 2025
278,000+tests run: code fixes, reasoning sessions and agent tasks
25models from 6 providers, on the same tests and schedule
2.1M+visits since launch
$0from AI model providers, and no affiliate links

Leaderboard

The five that lead each board.

Every model gets the same tasks and the same scoring. A free account shows every model on every board over 24 hours, 7 days and 30 days; a paid plan adds the scores from the newest run.

Top 5 · Last 30 days

  1. 1Claude Opus 5.5Score 97
  2. 2GPT-5.6 LunaScore 95
  3. 3DeepSeek V4.1 FlashScore 95
  4. 4GPT-5.5Score 93
  5. 5GPT-6 SolScore 93

Scores over the last 30 days, the same tasks for every model, each out of 100.

The real price of AI

Price per token isn’t price per result.

Every model gets the same tasks, and every attempt is priced at the provider’s list price. Divide what the attempts cost by the ones that succeeded and you get what a correct result really costs: on our coding tasks over the last 30 days, from $0.34 to $39.53 per 1,000 correct fixes. Pick the model you use and see what does as well for less.

Last 30 days · 29 Sep – 29 Oct

7 bug fixes in real code repositories. A fix counts only when the hidden tests pass.

Passed
77%
Cost per 1,000 correct fixes
$39.53
Typical attempt
17 s

Did at least as well, for less

  1. GPT-6 Luna85% · $0.34116× less
  2. GPT-5.6 Luna87% · $0.8049× less
  3. DeepSeek V4.1 Flash87% · $0.8547× less

Sorted by cost per 1,000 correct fixes, not by quality.

The same tasks for every model, 29 Sep – 29 Oct. Every attempt is priced at the provider’s list price; bars to scale. The router’s value modes do not simply take the cheapest: they only consider models within 5 points of the best score, then pick the cheapest of those.

AI drift detection

When a model quietly changes, you see it — and the router moves on.

Providers change models without changing the name. We have tested every model on a fixed schedule since August 2025, so a change leaves its mark in the record: in quality, in speed and in what each answer costs. A few of them:

  1. 12 Aug 2026

    2×longer answers

    DeepSeek V4 Pro

    A new build overnight. Answers twice as long (728 → 1,478 tokens) and 72% slower, under the same model name.

  2. 31 Jul 2026

    2×cost per correct answer

    DeepSeek V4 Flash

    A new build overnight. Answers twice as long (510 → 1,045 tokens), 64% slower, and each correct answer cost almost twice as much at the same price per token.

  3. March 2026

    −6 ptspass rate

    GLM-4.6

    Answers about a quarter longer (907 → 1,149 tokens), and its pass rate on the same tasks fell from 94% to 87%.

Illustration, not real data · how a reasoning score, its baseline and the detector look when a model driftsscoreown baselinePage-Hinkley

Smart Router · next request

auto-reasoning stops picking the flagged model and routes to the next healthy one. The routing reason names who was passed over, and why.

Flagged models drop behind healthy ones for every strategy that depends on that suite.

Watchlist · email

An email when a model you watch drops 5 points below where it was a week ago. Set your own threshold on paid plans.

Plus a summary every Monday of what moved and what held.

Teams · webhook

A signed callback to your own endpoint when a watched model regresses or a project reaches a budget threshold.

Per suite, per model

Coding, reasoning and tool use each run their own Page-Hinkley detector against the model’s own baseline, tuned on real run-to-run noise.

An hourly canary

Fixed probes run every hour; a sustained shift has to pass Welch’s t-test before it opens an incident.

Evidence, not vibes

Every flag points to the runs behind it. Full history and the diagnosis behind each change come with Pro.

Is your AI getting worse?How AI drift detection works

For teams building on AI

Benchmark the models on your own work.

Public scores tell you which model is best on our tasks. An assessment tells you which one is best on yours — measured by the same harness, the same scoring rules and the same statistics.

  1. 01

    Send up to 20 real tasks

    Prompts, files and the answers you would accept. We confirm the scope within 2 business days.

  2. 02

    We run 3 models of your choice

    In the same sandbox as the public leaderboard, with repeated trials so a lucky run can’t decide the result.

  3. 03

    Report in 7 business days

    Per-task results, cost and latency for each model, and our recommendation.

Sample reportBuilt from our public coding tasks, 29 Sep – 29 Oct
ModelPassedPer 1,000 correctTypical attempt
Claude Opus 5.593%$13.3218 s
GPT-6 Luna85%$0.343.5 s
Claude Fable 5.177%$39.5317 s

What the numbers sayGPT-6 Luna passed more often than Claude Fable 5.1, and each correct fix cost 116× less. Claude Opus 5.5 passed the most attempts, at 39× the cost of GPT-6 Luna per correct fix. On your own tasks the answer can be different, and that is what an assessment measures.

Then keep it running

Your own benchmark, wired into your router.

Our team builds a custom benchmark around your workflow — your tasks, your acceptance rules, your formats — and runs it continuously alongside our public suites. It connects to your Smart Router, so your requests keep going to whichever model is best on your work, and you hear about it when that changes.

  • Built by our team for your use case, from your real tasks.
  • Runs on our schedule, with drift alerts on your own suite.
  • Drives your router: the model that wins on your work gets your traffic.
$1,290One-off, paid at booking. Full refund if your tasks can’t be measured. Credited against an annual plan within 30 days.

Smart Router

Models change overnight. Your router should know.One endpoint. Fourteen ways to decide.

Point any OpenAI-compatible client at ASL’s Smart Router and every request goes to the model that is measurably best right now — for code, reasoning, tool use, speed or cost — ranked on the same results as this page. One endpoint, your own provider keys, zero markup on tokens. How it decides.

0%
markup on tokens. Providers bill you directly, at their own list price.
14
auto-* routing modes, from auto-coding to auto-cheapest.
10 min
between health checks on every provider the router can pick.
Smart Router · live routing decisions
Example requests · live router picks
Incoming requests
  1. auto-codingstream
    Fix the race condition in checkout.ts
    → GPT-5.6 Luna · 200
Model
auto-coding
Strategy
best_coding
Ranked on
Coding suite: real repository bug fixes, every 4 hours
Passed over
none
Routed to
GPT-5.6 Luna
Ranking for this requestCoding score
1GPT-5.6 LunaOpenAIrouted97.2
2DeepSeek V4.1 FlashDeepSeekfallback94.8
3Claude Opus 5.5Anthropicfallback97.3
4Claude Opus 4.7Anthropic93.2
5GPT-5.5OpenAI93.2
6GPT-5.6 SolOpenAI93.2
7GPT-5.6 TerraOpenAI93.2

Best overall

best_overall

The best combined score among the models you have keys for. When leaders are statistically tied, the one that costs less.

Ranks on
Combined score: coding 50%, reasoning 25%, tool use 25%
Ordered by
Quality, then the cheaper of tied leaders
Always
Only models you have a key for; drift-flagged models and open circuits go last
If you sent a request nowCombined score
1GPT-5.6 LunaOpenAIprimary94.4
2DeepSeek V4.1 FlashDeepSeekfallback93.7
3Claude Sonnet 5.5Anthropicfallback93.1
4Gemini 4 ArgonGoogle92.6
5Claude Opus 5.5Anthropic94.3
6GPT-5.6 TerraOpenAI92.2
7GPT-6 SolOpenAI91.9
Primary GPT-5.6 Luna fallback DeepSeek V4.1 Flash fallback Claude Sonnet 5.5
from openai import OpenAI

client = OpenAI(
    base_url="https://aistupidlevel.info/v1",
    api_key="aism_…",  # your ASL router key
)

reply = client.chat.completions.create(
    model="auto-best",
    messages=[{"role": "user", "content": prompt}],
    stream=True,
)

Response headers

HTTP/1.1 200 OK
X-AISM-Model: gpt-5.6-luna
X-AISM-Provider: openai
X-AISM-Reasoning: Selected gpt-5.6-luna from openai for best overall performance (combined benchmark) (94.4 ±1.5 over its last 5 measured runs). Statistically tied for first with deepseek-v4-flash, claude-sonnet-5-5, gemini-4-argon and 1 more; chosen as the cheapest of them ($0.044 per measured task). Tie-break: cheaper. Ranked #1 of 25 available models. Last measured 15d ago. Production: 993/993 succeeded in the last 14d, observed 5500ms.

Also speaks Anthropic: native /v1/messages passthrough, plus /v1/embeddings. Works with any client that lets you set a base URL. Router documentation

Get your router key →

Router internals

Built for agents in production.

A benchmark-driven pick is only half of a router. These are the details that decide whether it survives real traffic.

0% markup

Your keys, your bill

Requests go out with your own OpenAI, Anthropic, Google, DeepSeek, Moonshot and Z.ai keys, so providers bill you directly. We add nothing to token prices — plans include a number of routed requests.

Per suite

Drift-aware by default

When a model’s detector fires on the suite your strategy depends on — or it has an open canary incident — it drops behind healthy models. The routing reason names who was passed over.

5 fallbacks per request

Outages route around you

Each request carries up to 5 fallbacks: first from your own fallback order (a list of up to 10 models, skipping any that are unavailable), then the best models at other providers. A circuit opens after 5 straight failures and probes again after 60 seconds.

All six providers

Tool loops that don’t derail

Native tool calls with the provider’s own call ids, each model’s reasoning carried between turns, and a loop that stays on the model that started it. Forced tool_choice and json_schema work everywhere — natively, or emulated and checked.

32 MB · 15 min

Long context, long thinking

Native streaming on every provider, request bodies up to 32 MB for 1M-token contexts, and a 15-minute timeout for models that think before they answer.

Per key · per project

Budgets that hold

Hard and soft monthly budgets on every key and project, a maximum price per 1M tokens, a maximum latency, and provider or model exclusions — all checked before a request is sent.

X-AISM-Reasoning

Every pick explained

Each response names the model, the provider, the latency and why it won. Preview any routing setting against the real pipeline without spending a request.

AES-256-GCM

Private by default

Prompt logging is off unless you turn it on. Logged prompts are scrubbed of secrets before they are encrypted, and so are your provider keys.

14-day window

Learns from production

Real failures and your ratings through /v1/router/feedback adjust each model’s effective score, so a model that benchmarks well but fails in practice loses ground.

Benchmarks

Measured around the clock, not once a quarter.

The router is only as good as its data. Every model gets the same tasks, the same harness and the same scoring, on a fixed schedule — shown here in your time zone.

0003060912151821
Your time--:--Next health check in --:--
Provider healthA short completion to every provider with our own key. Failures are re-checked after 15 seconds.
Every 10 min144 a day
Canary drift probeFixed coding probes on every model, compared with its own history using Welch’s t-test.
Hourly24 a day
CodingReal repository bug fixes plus one hard function — 7 tasks, 7 attempts each.
Every 4 hours6 a day
CalibrationKnown unknowns: does a model say so when it can’t know the answer?
Every 6 hours4 a day
Reasoning · tool useMulti-turn engineering sessions checked by code, and sandboxed agent tasks with real tools.
Dailynight run
Robustness · bias · adversarialPrompt-variation, demographic and adversarial sweeps, run outside the score.
Unscoredseparate sweeps
Context rotLong-context accuracy from 8K to 1M tokens, by length and position. Pilot.
WeeklyPro and up
How every score is computed

Methodology public. Test tasks private, so no lab can train on them.

Provider status

Every provider, checked every 10 minutes.

A short completion goes to each provider with our own key, day and night. Failures are re-checked 15 seconds later and attributed, so the router only avoids real outages — and the status page never blames a vendor for our problem.

All 6 providers answering · last check —Next check in --:--
ProviderNowLatencyLast 7 days, hourlyUptime
OpenAIOperational1.5 s
100%
AnthropicOperational1.2 s
100%
GoogleOperational664 ms
100%
DeepSeekOperational1.1 s
100%
Moonshot AIOperational2.1 s
100%
Z.aiOperational1.9 s
100%
OperationalDegradedProvider outageOur side — not counted against the provider
Provider

Unreachable twice while our side is healthy. Opens an incident; the router stops sending traffic.

Our account

A billing or quota answer for our own key. Logged, never shown as the provider’s outage.

Probe

A malformed or timed-out check of our own making. Re-run, not reported.

Our server

Several providers failing together, or our own network down. The router keeps routing.

Open the live status page

Data API

Every score, as JSON.

Keyed access to scores, history, drift and incidents — for dashboards, CI gates and model reviews. Build against the free key at 10 requests a day; production tiers go up to 250,000 a day.

GET /api/v1/models/:id/historyasl_ key
curl https://aistupidlevel.info/api/v1/models/292/history?period=7d \
  -H "X-API-Key: $ASL_DATA_KEY"
{
  "success": true,
  "period": "7d",
  "data": {
    "dataPoints": 41,
    "data": [
      { "timestamp": "2026-10-14T10:00:00Z", "score": 86,
        "suite": "combined", "axes": { … } },
      …

Data API documentation

Watchlist & alerts

Know before your users do.

Pick the models you depend on. We tell you when one of them slips — by email, in a weekly summary, or by webhook into your own tools.

  • 3 models free, 20 on Pro and Developer, unlimited on Teams.
  • Email when a watched model falls 5 points below where it was a week ago. Set your own thresholds on paid plans.
  • A weekly summary every Monday of what moved and what held.
  • Signed webhooks for regressions and budget thresholds, and a team watchlist that alerts everyone in the workspace.

Pricing

Start free. Pay when the router earns it.

Free

$0forever

No card required

The public evidence, plus a watchlist of three models with email alerts and a weekly summary.

Create free account

Includes

  • 3 tracked models, with email alerts
  • 30 days of history
  • Every category ranking
  • Smart Router: 1,000 requests a month
  • Data API: 10 requests a day

Pro Intelligence

$120/ year

$10 a month · save $24

The drift monitor and the full leaderboard analysis, full history, calibration and substitute analysis, exports and custom alerts.

Start free trial

Everything in Free, plus

  • 20 tracked models and custom alert thresholds
  • The drift monitor, quick answers, heatmap, radar and price-performance
  • Full history and the drift diagnosis behind every change
  • Calibration and cheaper-substitute analysis
  • Context-rot pilot: long-context accuracy up to 1M tokens
  • Routing analytics and CSV/JSON exports
  • Smart Router: 10,000 requests a month
  • Data API: 10,000 requests a day

Developer

$250/ year

$20.83 a month · save $50

For running the Smart Router in production: ten times the requests, API monitoring and 30-day decision logs.

Start free trial

Everything in Pro, plus

  • Smart Router: 100,000 requests a month
  • API monitoring: per-key logs, costs, prompt auditing and budget limits
  • 30-day decision logs
  • Data API: 25,000 requests a day
  • A workspace with one project and a shared watchlist; viewers free

TeamsMost complete

$1,290/ year

$107.50 a month · save $258

Five editors, each with the full Teams plan, three projects with their own router keys, budgets and spend reports, plus webhooks, single sign-on and an audit trail.

Start free trial

Everything in Developer, plus

  • 5 editors, each with the full Teams plan
  • 3 projects, each with its own router keys, rules, budget and spend report
  • A team watchlist with alerts to everyone
  • Smart Router: 1,000,000 requests a month
  • 90-day decision logs
  • Data API: 100,000 requests a day
  • Webhooks for regressions and budgets
  • Single sign-on (OIDC or SAML), SCIM and an audit trail

EnterpriseContracted scope, unlimited seats and requests, 365-day decision logs and invoicing. 250,000 Data API calls a day.

Talk to us

Past your router allowance? Top up credits from $5 — 2,000 requests per $1, no expiry. Providers bill your tokens directly; we never add to them. Compare every plan

FAQ

Questions people actually ask.

Still unsure? The methodology explains every number on the site, and the full FAQ covers the rest.

Are AI models really getting worse over time?

Sometimes — and usually without notice. Providers change weights, safety layers and serving infrastructure behind the same model name. AI Stupid Level re-runs the same tasks on every model on a fixed schedule and compares each one with its own history, so a drop shows up as data instead of a hunch. Is your AI getting worse? gives the answer by provider.

Is ChatGPT getting worse? Is Claude getting worse?

Check the record: is ChatGPT getting worse and is Claude getting worse each read the drift detectors and the 24-hour board for that family. Every OpenAI and Anthropic model we track is re-tested on coding every 4 hours and on reasoning and tool use every day, and a model is flagged only when a change holds up statistically — not after one bad run.

What does “cost per correct fix” mean?

What we paid the provider, at its list price, for every attempt at a task, divided by the attempts that passed the hidden tests. A model that is cheap per token but fails often can cost more per correct result than a pricier one that gets it right, so this is the number that tells you what the work really costs.

Which AI model is best for coding right now?

It changes, which is the point. The leaderboard ranks every model we track on real repository bug fixes every 4 hours — which model is best for coding shows the 24-hour board — and the router’s auto-coding mode sends your request to the current leader among the models you have keys for.

How is the Smart Router different from other LLM routers?

It routes on measured quality, not just price and uptime. Rankings come from our own continuous benchmarks, drift-flagged models drop behind healthy ones, and every response explains its pick in an X-AISM-Reasoning header. You keep your own provider keys and pay providers directly.

Can you test the models on our own tasks?

Yes. A workload assessment runs up to 20 of your real tasks on three models in our harness, with a report in 7 business days. Our team can also build a custom benchmark around your workflow, run it continuously alongside our public suites, and connect it to your Smart Router, so your requests keep going to the model that is best on your work.

Do you mark up tokens or resell inference?

No. Requests are sent with your own provider keys and billed to you by the provider at their list price. Plans include a monthly number of routed requests; past that you can top up credits or move up a plan.

Which providers and models do you cover?

OpenAI, Anthropic, Google, DeepSeek, Moonshot AI (Kimi) and Z.ai (GLM). The router handles text, code and tool calls. It does not route images or audio, because we do not measure them and will not route what we do not measure.

Why do I need an account to see the leaderboard?

A free account costs nothing and includes every category ranking over the last 24 hours, 7 days and 30 days, a three-model watchlist with email alerts, 1,000 routed requests a month and a Data API key. The newest run, as it lands, is part of the paid plans. Model pages, the methodology and the status page stay open to everyone.

Stop guessing which model is best today.

Create a free account to see every ranking, watch three models and route your first 1,000 requests — with your own keys.