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LeaderboardEvery tracked model, ranked and priced side by sideBenchmarksWhat each test measures and who leads itPricesAPI, media, and hardware rates with a cost calculator

Plan

Stack plannerSix questions to a priced local and hosted stackShortlistOur picks for subscriptions, APIs, and hardwareEnterpriseSeat plans against self-hosting for a whole team

Build

HardwareGPUs and workstations, and which models they fitHostsWhere to rent open-weight inference, and for how muchHarnessesCoding agents and the models they drive

Lab

FindingsResults from our own evaluationsScanAudit a repo’s AI usage in the browserMethodWhere the numbers come from and how we check them
Data checked September 25, 2026
Data checked September 25, 2026
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T/TTokens or Towers

An independent guide to AI models, what they cost, and the hardware to run them. No account, no API key, no sponsors.

Compare

  • Leaderboard
  • Benchmarks
  • Prices

Plan

  • Stack planner
  • Shortlist
  • Enterprise

Build

  • Hardware
  • Hosts
  • Harnesses

Lab

  • Findings
  • Scan
  • Method
Data checked September 25, 2026 · Every number links to its sourceRSS · Source on GitHub

Independent AI model guide · Updated September 25, 2026

Know which model is worth it, and what it costs to run.

267 language, image, and video models from 66 labs, ranked on independent benchmarks and priced from the source. Then a planner that tells you whether to rent tokens or buy the tower.

Open the leaderboard →Plan a stack

Top of the index

AA Intelligence v4.3
  1. 01AnthropicClaude Opus 5.5Anthropic57.6
  2. 02MetaMuse Wonder FullMeta56.0
  3. 03AnthropicClaude Sonnet 5.5Anthropic56.0
  4. 04AnthropicClaude Fable 5.1Anthropic53.4
  5. 05GoogleGemini 4 ArgonGoogle53.0
  6. 06OpenAIGPT-6 AstraOpenAI52.7

Best open weights: MiMo-V2.6-Pro at 46.3, 11.3 points behind.

Models tracked
267
Benchmarks explained
32
Sourced scores
2,010
Labs covered
66

The frontier

Capability is getting cheaper. Not every price has noticed.

Each dot is a model: how it scores against what a million tokens costs. The line connects the models that nothing cheaper beats. MiMo-V2.6-Pro keeps 80% of Claude Opus 5.5’s score at $0.57 per million tokens, 16× cheaper.

Full leaderboard →

Intelligence Index against blended price

92 language models with an independent index score and a list price. Blended price is 70% input, 30% output.

  • Closed weights
  • Open weights
  • Efficient frontier
010203040506070$.1$.3$1$3$10$30BLENDED PRICE, $ PER MILLION TOKENS (LOG) →↑ AA INTELLIGENCE INDEXClaude Fable 5.1Muse Spark 1.3Claude Opus 5.5Claude Sonnet 5.5Claude Haiku 5.5MiMo-V2.6-ProTencent Hy3Nemotron 3.5 Lightning 30B A3BGranite 4.2 3B
View as table
Intelligence Index against blended price
ModelProviderAA Intelligence IndexBlended $/MFrontier
Claude Opus 5.5Anthropic57.6$8.80Yes
Claude Sonnet 5.5Anthropic56$4.40Yes
Claude Fable 5.1Anthropic53.4$22.00
Gemini 4 ArgonGoogle53$4.40
GPT-6 AstraOpenAI52.7$22.00
GPT-6.1 SolOpenAI52$4.40
Muse WonderMeta52$8.80
Claude Opus 5Anthropic50.8$11.00
Claude Fable 5Anthropic49.6$22.00
Muse Spark 1.3Meta48.1$2.15Yes
GPT-6 SolOpenAI47.5$4.40
GPT-5.6 SolOpenAI47$8.80
Grok 4.7xAI46.4$3.20
MiMo-V2.6-ProXiaomi46.3$0.57Yes
Qwen3.8-MaxAlibaba45$3.20
GLM-5.3Z.ai45$2.30
Grok 4.6xAI44.3$3.20
Kimi K3Moonshot AI44$6.60
Step 5 PreviewStepFun43.7$1.51
Claude Haiku 5.5Anthropic43$0.22Yes
GPT-5.6 TerraOpenAI42.1$5.00
GLM-5.3-FlashZ.ai42$0.26
Claude Opus 4.8Anthropic41.8$11.00
Gemini 3.8 FlashGoogle40.9$1.65
Qwen3.8-2.4T-A95BAlibaba40$3.20
Muse Spark 1.2Meta39.6$2.15
Gemini 3.7 FlashGoogle39.1$1.65
DeepSeek V4.1 FlashDeepSeek39$0.57
Grok 4.5xAI38.8$3.20
Claude Sonnet 5Anthropic38.2$4.40
Mistral Large 4Mistral38$2.21
GPT-6 LunaOpenAI37.3$0.22
GPT-5.6 LunaOpenAI37.3$0.50
DeepSeek V4 Pro (0813)DeepSeek36$2.11
Gemini 3.6 FlashGoogle34$1.65
Qwen3.8-27BAlibaba34$1.25
GLM-5.2Z.ai34$2.30
Muse Spark 1.1Meta33.7$2.15
Gemini 3.5 FlashGoogle32.6$3.75
GPT-5.3 CodexOpenAI32.5$5.43
Gemini 3.1 Pro PreviewGoogle29.7$5.00
Qwen3.7-MaxAlibaba29$4.00
MiniMax-M3MiniMax29$0.57
GLM-5Z.ai28$1.66
Inkling-SmallThinking Machines Lab27.8$0.57
Grok Build 0.1xAI27.2$1.30
Kimi K2.6Moonshot AI27$1.87
Quasar 438BMultiverse Computing26.7$0.96
Apodex 1.1Apodex26.4$1.11
Kimi K2.7 CodeMoonshot AI26$1.87
MiMo-V2.5-ProXiaomi26$0.57
Tencent Hy3Tencent25.3$0.16Yes
MiMo-V2.5Xiaomi25.2$0.18
Qwen3.7-PlusAlibaba25$0.76
InklingThinking Machines Lab25$1.92
Grok 4.3xAI24.9$1.63
GPT-5.4 miniOpenAI24.1$1.88
Solar Mini 4Upstage24$0.19
MiniMax-M2.7MiniMax23$0.57
Nemotron 3 Ultra 550B A55BNVIDIA22.9$1.17
Gemini 3.5 Flash-LiteGoogle22.2$0.96
Qwen3.6-27BAlibaba21$1.50
GPT-5.4 nanoOpenAI20.7$0.52
Step 3.7 FlashStepFun19.5$0.49
LongCat-2.0Meituan19.1$1.41
Qwen3.6-35B-A3BAlibaba18$0.94
Claude Haiku 4.5Anthropic16.9$2.20
Granite 4.2 30BIBM14.8$0.31
Mistral Medium 3.5Mistral14.2$3.30
Amazon Nova 2 Pro (Preview)Amazon14.2$3.88
Amazon Nova 2 Omni (Preview)Amazon13.6$0.96
Amazon Nova 2 LiteAmazon13.4$0.96
Nemotron 3.5 Lightning 30B A3BNVIDIA12.9$0.12Yes
Nemotron 3 Super 120B A12BNVIDIA12.8$0.48
Mercury 2.5Inception12.3$0.40
Mistral Small 4Mistral11.3$0.29
Granite 4.2 8BIBM11.1$0.12
Trinity Large ThinkingArcee AI10.8$0.42
Nemotron 3 Nano Omni 30B A3B ReasoningNVIDIA10.3$0.47
Mistral Large 3Mistral9.3$0.80
Granite 4.2 3BIBM9.1$0.06Yes
Nemotron 3 Nano 30B A3BNVIDIA8.9$0.10
Hermes 4 405BNous Research7.5$1.60
Amazon Nova ProAmazon7$1.52
Command ACohere7$4.75
Amazon Nova LiteAmazon6.7$0.11
Ministral 3 14BMistral6$0.20
Amazon Nova MicroAmazon5.9$0.07
Reka Flash 3Reka AI5.6$0.38
Ministral 3 8BMistral5.5$0.15
Apertus 70B InstructSwiss AI Initiative5.1$1.45
Ministral 3 3BMistral4.8$0.10

Who leads what

There is no best model. There is a best model for the job.

The overall index hides a lot. These are the leaders on the tests closest to real work, with the runner-up so you can see how close the race is.

How each test works →
  • Fixing real repositories

    AnthropicClaude Opus 5.5

    89.9%vendor

    SWE-bench Pro · next: Claude Sonnet 5.5 81.3%

  • Working in a terminal

    AnthropicClaude Sonnet 5.5

    70.6%vendor

    Terminal-Bench 4.0 · next: Claude Mythos 5.1 60.9%

  • Following policy with tools

    Z.aiGLM-5.2

    99.1%

    τ²-Bench · next: Claude Fable 5 98.5%

  • Expert-level questions

    AnthropicClaude Sonnet 5.5

    64.5%vendor

    Humanity’s Last Exam · next: Claude Opus 5.5 61.4%

  • Generating video

    AlibabaWan 3.0

    1156

    Artificial Analysis Video Arena: text to video with audio · next: Utopai X 1149

  • Generating images

    OpenAIGPT Image 2.5 Sunburst

    1196

    Artificial Analysis Image Arena: text to image · next: GPT Image 2.5 Flare 1190

Just released

The newest models, already on the board.

See every model →
  • MetaOct 12Muse WonderMetaIndex52.0In / out per 1M$4.00 / $20.00
  • AnthropicOct 7Claude Haiku 5.5AnthropicIndex43.0In / out per 1M$0.10 / $0.50
  • ShengShuOct 7Vidu Q4 PreviewShengShuIndex—Price$0.08 per second of 1080p video, as listed by Artificial Analysis ($5.04/min); Vidu has not published Q4 on its pricing page
  • MistralOct 6Mistral Large 4MistralIndex38.0In / out per 1M$1.36 / $4.18
  • GoogleOct 6Nano Banana 2.1GoogleIndex—In / out per 1M$1.50 / $30.00
  • Reflection AIOct 5BeamReflection AIIndex—In / out per 1MNo list price
  • Aleph AlphaOct 3Kolibri-1Aleph AlphaopenIndex—In / out per 1MSelf-host
  • xAIOct 1Grok Imagine Video 1.5 LitexAIIndex—Price$0.02 per second of video (xAI lists one rate; Artificial Analysis lists $8.40/min at 1080p)

Four ways in

Compare, plan, build, then check our work.

01

Compare

  • ▲LeaderboardEvery tracked model, ranked and priced side by side
  • ≡BenchmarksWhat each test measures and who leads it
  • $PricesAPI, media, and hardware rates with a cost calculator

02

Plan

  • →Stack plannerSix questions to a priced local and hosted stack
  • ★ShortlistOur picks for subscriptions, APIs, and hardware
  • ◧EnterpriseSeat plans against self-hosting for a whole team

03

Build

  • ▣HardwareGPUs and workstations, and which models they fit
  • ☁HostsWhere to rent open-weight inference, and for how much
  • ⌘HarnessesCoding agents and the models they drive

04

Lab

  • ◎FindingsResults from our own evaluations
  • ⌕ScanAudit a repo’s AI usage in the browser
  • §MethodWhere the numbers come from and how we check them

From the lab

We test the claims ourselves.

All findings →
  • August 5, 2026GPT-5.6 Luna matched Sol on our hardest question classPick models per task class with your own measurements, because the aggregate ranking hides exactly the crossovers that save money.

Stack planner

Six questions. Three priced stacks.

Tell us the work, the data rules, and the budget. The planner weighs every API price against hardware you could own and shows the math behind each pick.

Plan a stack →