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Kimi K3 (Max)

open weights★ featured
Moonshot AI · released 2026-07-16 · 35 offers

Context 1M tokens

Top 5 cheapest providers (Adjusted $/task)

The same list price can give a different adjusted $/task (caching, token efficiency) — click a price for its inputs.

Within the active global provider, residency and confidentiality filters.

#ProviderAdjusted $/task
1Relacevia OpenRouter — Price via OpenRouter: OpenRouter's price for Relace's endpoint (https://openrouter.ai/moonshotai/kimi-k3/providers), collected 2026-11-03.
2Wafervia OpenRouter — Price via OpenRouter: OpenRouter's price for Wafer's endpoint (https://openrouter.ai/moonshotai/kimi-k3/providers), collected 2026-11-03.
3Sail Researchvia OpenRouter — Price via OpenRouter: OpenRouter's price for Sail Research's endpoint (https://openrouter.ai/moonshotai/kimi-k3/providers), collected 2026-11-03.
4Makoravia OpenRouter — Price via OpenRouter: OpenRouter's price for Makora's endpoint (https://openrouter.ai/moonshotai/kimi-k3/providers), collected 2026-11-03.
5InferenceNetvia OpenRouter — Price via OpenRouter: OpenRouter's price for InferenceNet's endpoint (https://openrouter.ai/moonshotai/kimi-k3/providers), collected 2026-11-03.

Composite

6 of 7 inputs · 4 from the model family6 radar axes: DesignArena's two boards share one

75.4

includes −2.9 for its Benchmaxxing signal (from 78.3; why, switch off in Options)

AA Coding v4.xCoding Agent v1.4AA Intelligence (est.)AA AgenticEpoch ECISoftware ECIDesignArenaAA Coding v4.x: percentile 92AA Intelligence (est.): percentile 93AA Agentic: percentile 92Epoch ECI: percentile 73Software ECI: percentile 76DesignArena: percentile 87

AA Coding v4.x 76.2Coding Agent v1.4 —AA Intelligence (est.) 33.4AA Agentic 50.6Epoch ECI 158.3Software ECI 160.8DesignArena 1282/1315

Radar: percentile among all models measured on each input; a gap means not measured.

Benchmark sheet

66 of 319 registered benchmark versions · bars show the percentile among all models measured on each benchmark.

Composite attachments (used in the score, not counted as exact benchmarks):
  • Epoch ECI · attached
  • Software ECI · attached
  • DesignArena Web Apps (agentic) · attached
  • DesignArena Full-Stack · attached
Compare this model →

Agentic

  • AA-AnalystAgent5838.8%

    AA-AnalystAgent published 2026-09-10 → · Published board — Tests analyst tasks using agentic Python execution across fourteen domains.

  • APEX-Agents-AA9741.3%

    APEX-Agents-AA published 2026-09-10 → · Published board — Tests professional-service tasks that require agents to produce locally graded deliverables.

  • AA-Briefcase901,497 Elo

    AA-Briefcase published 2026-09-10 → · Published board — Tests multi-week professional knowledge-work projects with linked tasks and large source collections.

  • GDPval-AA v2921,584 Elo

    GDPval-AA v2 v2 → · Published board — Tests professional knowledge-work deliverables across occupations using AA's Stirrup harness.

  • Harvey LAB-AA9894.6%

    Harvey LAB-AA published 2026-09-10 → · Published board — Tests legal-work deliverables across practice areas on Harvey's private task set. Artificial Analysis' run, graded by one LLM judge against task rubrics — not the same run or scale as Vals AI's HLAB row.

  • ITBench-AA9447.7%

    ITBench-AA published 2026-09-10 → · Published board — Tests root-cause diagnosis from offline Kubernetes incident snapshots.

  • Terminal-Bench v2.1 (AA)8985.0%

    Terminal-Bench v2.1 (AA) v2.1 → · Published board — Tests terminal-based work on the 89-task verified refresh using Terminus 2.

  • Terminal-Bench v4.0 (AA)7312.6%

    Terminal-Bench v4.0 (AA) v4.0 → · Published board — Tests terminal-based work on the 66-task release using mini-SWE-agent v2.4.6.

  • ApprenticeBench API (NeoCognition)4625.0%

    ApprenticeBench API (NeoCognition) published 2026-09-14 → · Claude Code — An agent completes the same 100 sequential accounts-payable tasks in the Odoo ERP with diminishing mentoring, using dedicated application API calls instead of the screen interface.

  • ApprenticeBench CUA (NeoCognition)3118.0%

    ApprenticeBench CUA (NeoCognition) published 2026-09-14 → · Claude Code — A computer-use agent operates the Odoo ERP through its screens across 100 sequential accounts-payable tasks with diminishing mentoring.

  • τ²-Bench Airline (OpenRouter run)5270.9%

    τ²-Bench Airline (OpenRouter run) published 2026-09-15 → · Published board — Multi-turn service agents making tool calls under strict policy constraints. (OpenRouter's own reproducible run, as published on openrouter.ai/benchmarks.)

  • HLAB — Harvey's Legal Agent Benchmark (Vals Index v2)7310.8%

    HLAB — Harvey's Legal Agent Benchmark (Vals Index v2) v2 → · Published board — Long-horizon legal work product creation. The index column is Harvey's Legal Agent Benchmark's own published standalone score, reported as accuracy — not comparable with Artificial Analysis' Harvey LAB-AA row.

  • Scale SEAL: SWE-Bench Pro V2 HARD6988.2

    Scale SEAL: SWE-Bench Pro V2 HARD published 2026-09-22 → · Published board — Scale SEAL: SWE-Bench Pro V2 HARD results published by Scale AI.

  • Time Horizon Index: KSP010.5%

    Time Horizon Index: KSP published 2026-09-14 → · Published board — Time Horizon Index: KSP results published by Vals AI.

  • Terminal-Bench 4.02512.6%

    Terminal-Bench 4.0 published 2026-09-22 → · Published board — Terminal-Bench 4.0 results published by Vals AI.

  • Terminal-Bench Science252.9%

    Terminal-Bench Science published 2026-09-23 → · Published board — Terminal-Bench Science results published by Vals AI.

  • Tax Agent Bench6768.7%

    Tax Agent Bench published 2026-09-23 → · Published board — Tax Agent Bench results published by Vals AI.

  • LMArena Agent Arena (overall net improvement)534.5%

    LMArena Agent Arena (overall net improvement) published 2026-09-26 → · Published board — Ranking of models as the orchestrator in LMArena’s Agent Mode, scored by the causal net improvement over the average model across behavioural signals from real sessions.

  • AA Agentic Index9250.6

    AA Agentic Index published 2026-09-18 → · Published board — Artificial Analysis publishes one Agentic Index per model, measured on its primary configuration and relayed by OpenRouter's Benchmarks API; the value is attached at family scope on the deterministic representative. Artificial Analysis publishes this board without a version number; we keep the date each result was retained.

Coding

  • Artificial Analysis Coding Agent Index v2.0no percentile41.4%

    Artificial Analysis Coding Agent Index v2.0 v2.0 → · Kimi Code CLI — Measures coding-agent systems on FrontierCode v1.1 Main, Terminal-Bench 4.0 and SWE-Atlas-QnA-AA.

  • SciCode (AA subproblems) v1.0.19659.5%

    SciCode (AA subproblems) v1.0.1 → · Published board — Tests scientific Python programming with scientist-annotated background information.

  • DeepSWE (Datacurve, via Epoch AI)7168.5%

    DeepSWE (Datacurve, via Epoch AI) published 2026-09-15 → · mini-SWE-agent — Pass rate of coding agents on original, long-horizon software engineering tasks, run by Datacurve with the mini-swe-agent harness.

  • FrontierSWE v25725.9%

    FrontierSWE v2 v2 → · proximus — 34 hand-written real-world software tasks: every model is evaluated with the site’s own Proximus harness at its maximum reasoning effort, 5 trials per task under a 20-hour budget, scored by the site’s own review protocol; the headline value is mean@5 in percent with best@5/worst@5 bounds.

  • Code Migration (Vals Index v2 subset)1516.0%

    Code Migration (Vals Index v2 subset) v2 → · Published board — Porting projects to another language, including COBOL modernization.

  • MLS-Bench-Lite 30-tasksno percentile48.3

    MLS-Bench-Lite 30-tasks → · Kimi-Code (max) — AI agents get a fixed ML research scaffold with strong baselines and must invent one algorithmic change — a loss, optimizer, sampler or training procedure — whose gain holds across settings, seeds, datasets and scales; Lite is the 30-task subset over all 12 research domains.

  • Vibe Code Bench 1-1001718.2%

    Vibe Code Bench 1-100 published 2026-09-22 → · Published board — Vibe Code Bench 1-100 results published by Vals AI.

  • Code Migration (standalone Vals board, 2026-09-22 snapshot)816.1%

    Code Migration (standalone Vals board, 2026-09-22 snapshot) published 2026-09-22 → · Published board — Standalone Code Migration results published by Vals AI, distinct from its Vals Index v2 subset.

  • Scale SEAL: SWE-Bench Pro V2 Full7897.7%

    Scale SEAL: SWE-Bench Pro V2 Full published 2026-09-26 → · Published board — Scale AI’s refreshed public SWE-Bench Pro split (642 long-horizon tasks in 11 copyleft repositories) run under a locked protocol, scored by resolve rate.

  • LMArena WebDev (Code Arena, overall)711,660 Elo

    LMArena WebDev (Code Arena, overall) published 2026-09-26 → · Published board — Community pairwise-vote ranking of models on front-end web development tasks, including agentic multi-step coding, published by LMArena as a Bradley-Terry rating.

  • AA Coding Index v4.x · frozen 2026-10-279276.2

    AA Coding Index v4.x · frozen 2026-10-27 → · Published board — Artificial Analysis withdrew the Coding Index with Intelligence Index v5.0 (2026-10-28). These are the last v4.x values, frozen with their own date (2026-10-27).

  • DesignArena Web Apps (agentic)831,282 Elo

    DesignArena Web Apps (agentic) published 2026-11-03 → · Published board — Published Elo. Exact source attachment is retained; fewer than 200 battles excludes a row from radar normalization and anomaly peers.

  • DesignArena Full-Stack961,315 Elo

    DesignArena Full-Stack published 2026-11-03 → · Published board — Published Elo. Exact source attachment is retained; fewer than 200 battles excludes a row from radar normalization and anomaly peers.

Efficiency

Instruction-following

  • LisanBench word chains, v0.2.0 (Lisan al Gaib)9610,521

    LisanBench word chains, v0.2.0 (Lisan al Gaib) v0.2.0 → · Published board — A model builds the longest chain of English words it can, each differing from the last by one letter, with no repeats and only dictionary words, from 50 starting words; any broken rule ends the chain.

Knowledge

Long-context

  • GDP.pdf (AA)8322.0%

    GDP.pdf (AA) published 2026-09-10 → · Published board — Tests professional reasoning over long PDFs with AA document preparation and grading.

  • AA-LCR v1.110088.7%

    AA-LCR v1.1 v1.1 → · Published board — Tests reasoning across multiple long documents with corrected answer keys and grading.

  • MLCR-AA8638.3%

    MLCR-AA published 2026-09-10 → · Published board — Tests medical-record synthesis and reasoning across long, fragmented case documents.

  • Context Arena — MRCR v2 (8-needle)3373.3%

    Context Arena — MRCR v2 (8-needle) 8-needle → · Published board — The model must find and reproduce the right one of eight near-identical earlier replies hidden in a long conversation, averaged over context lengths from 8k to 128k tokens.

Math

  • FrontierMath Tier 4 v2 (Epoch AI)5339.0%

    FrontierMath Tier 4 v2 (Epoch AI) v2 → · Published board — The hardest, research-level tier of Epoch AI's unpublished FrontierMath problems, run by Epoch AI on its private v2 set.

  • FrontierMath Tiers 1–3 v2 (Epoch AI)6672.2%

    FrontierMath Tiers 1–3 v2 (Epoch AI) v2 → · Published board — Unpublished, expert-written mathematics problems from undergraduate to research level with automatically checkable answers, run by Epoch AI on its private v2 set.

  • IOI1048.9%

    IOI published 2026-09-23 → · Published board — IOI results published by Vals AI.

Reasoning

  • ARC-AGI-14694.5%

    ARC-AGI-1 v1 → · Published board — The first-generation ARC-AGI benchmark measuring passive fluid intelligence, with leaderboard score plotted against cost-per-task.

  • ARC-AGI-22660.4%

    ARC-AGI-2 v2 → · Published board — The second-generation ARC-AGI benchmark of passive fluid intelligence, with leaderboard score plotted against cost-per-task.

  • Chess Puzzles (Epoch AI)7239.0%

    Chess Puzzles (Epoch AI) published 2026-09-18 → · Published board — Best-move selection on 100 novel chess positions generated programmatically by Epoch AI, each with a single Stockfish-verified best move; probes spatial reasoning and planning.

  • Mystery Game Puzzles (Epoch AI)3926.0%

    Mystery Game Puzzles (Epoch AI) published 2026-09-18 → · Published board — Best-move selection on 100 mid-game positions of a well-known game whose identity Epoch deliberately keeps undisclosed, generated programmatically like Chess Puzzles.

  • SimpleBench8860.7%

    SimpleBench published 2026-09-10 → · Published board — A multiple-choice text benchmark of over 200 questions covering spatio-temporal reasoning, social intelligence, and linguistic adversarial robustness, on which a non-specialized human baseline outperforms every tested LLM.

  • SimpleBench8860.7%

    SimpleBench published 2026-09-26 → · Published board — A multiple-choice text benchmark of over 200 questions covering spatio-temporal reasoning, social intelligence, and linguistic adversarial robustness, on which a non-specialized human baseline outperforms every tested LLM.

Science

Tool-use

  • AutomationBench-AA v1.0.68658.3%

    AutomationBench-AA v1.0.6 → · Published board — Tests multi-app SaaS workflows through REST tools on a held-out AutomationBench split.

  • EnterpriseOps-Gym-AA7945.3%

    EnterpriseOps-Gym-AA published 2026-09-10 → · Published board — Tests enterprise workflows through MCP tools against resettable application environments.

  • τ³-Banking (AA) v1.0.19546.0%

    τ³-Banking (AA) v1.0.1 → · Published board — Tests banking support agents that retrieve policies and change account state through tools.

  • MCP Atlas (Scale AI)8682.3%

    MCP Atlas (Scale AI) published 2026-09-21 → · Published board — How reliably a model completes realistic multi-step workflows over real Model Context Protocol servers: discovering the right tool in a noisy tool menu, calling it with correct parameters, recovering from errors and synthesising the results into an accurate final answer.

  • Toolathlon-Verified (HKUST NLP) 2026-06-3010076.5%

    Toolathlon-Verified (HKUST NLP) 2026-06-30 → · Published board — An agent completes 108 real-world tool-use tasks across 32 MCP servers and 7 local toolkits, and each task is graded by executing the resulting state against the task's ground truth.

  • Excel Modeling Benchmark (Vals Index v2)6466.4%

    Excel Modeling Benchmark (Vals Index v2) v2 → · Published board — Building and editing financial models in spreadsheets.

  • MCPMark Verified10096.1%

    MCPMark Verified verified → · Published board — AI agents complete realistic multi-step tasks through Model Context Protocol servers for Notion, GitHub, a filesystem, Postgres and a Playwright browser, each checked by the task's own verification script; Verified is the maintainers' version-pinned, stabilized 127-task set.

  • Excel Modeling Benchmark (standalone Vals board, 2026-09-22 snapshot)3666.4%

    Excel Modeling Benchmark (standalone Vals board, 2026-09-22 snapshot) published 2026-09-22 → · Published board — Standalone Excel Modeling Benchmark results published by Vals AI, distinct from its Vals Index v2 subset.

Vision

  • MMMU Pro (AA)8680.5%

    MMMU Pro (AA) published 2026-09-10 → · Published board — Tests multimodal understanding using challenging ten-option questions.

  • Chartography 100-tasks3926.6%

    Chartography 100-tasks → · Published board — Can a model read the charts professionals rely on — Kaplan-Meier curves, candlesticks, contour maps, Sankey diagrams, Bode plots, wind roses — from the image alone, to an expert-set precision?

  • GDP.pdf 100-tasks2919.0%

    GDP.pdf 100-tasks → · Published board — Can a model answer real professional questions about the PDFs work runs on — manuals, wiring diagrams, filings, forms — so that every rubric criterion an expert wrote is met?

  • Furniture Assembly Benchmark (Epoch AI)4034.2%

    Furniture Assembly Benchmark (Epoch AI) published 2026-09-26 → · Published board — Spatial-reasoning test by Epoch AI: given a photo of a partly or fully assembled IKEA product and its official manual, the model must say whether the build is correct and, if not, name the step with the mistake.

Unusual results

2 threshold-crossing signals flagged · 43 eligible benchmark families

How flags are calculated

Heuristic screen, not statistical significance: benchmark families are correlated and source uncertainty is unknown. Peer evidence needs ≥ 20 independently measured matched configurations from ≥ 10 distinct model families. A flag needs a directed population z-score of magnitude ≥ 1.5 and a gap of ≥ 1.5 from the leave-one-benchmark-family-out mean z in the same direction, over ≥ 5 other benchmark families.

  • unusually strong CritPt (AA) published 2026-09-10
    Why
    Observed: 0.23429 fraction
    Peer mean 0.04412 · peer sd 0.08179 · n 537 · families 370
    Directed z 2.325 · baseline z 0.711 · gap 1.614 · profile n 42
    0.23429 fractionmeasuredobserved 2026-09-10artificialanalysis.ai ↗
    Evidence
    Axis: CritPt (AA) · published 2026-09-10 · Published board
    Exact value: 0.234285714285714 fraction
    Observed: 2026-09-10T21:47:16.627Z · publication date: not recorded
    Observation id: aa:f7d2fc3e-1f7b-405f-818c-07952a4af78f:critpt
  • unusually strong LisanBench word chains, v0.2.0 (Lisan al Gaib)
    Why
    Observed: 10520.67 points
    Peer mean 2254.67038 · peer sd 3623.30948 · n 52 · families 44
    Directed z 2.281 · baseline z 0.712 · gap 1.569 · profile n 42
    10520.67 pointsmeasuredobserved 2026-09-16lisanbench.com ↗
    Evidence
    Axis: LisanBench word chains, v0.2.0 (Lisan al Gaib) · v0.2.0 · Published board
    Exact value: 10520.67 points
    Observed: 2026-09-16T19:06:45.428158+00:00 · publication date: not recorded
    Observation id: public:fc8754ca00235bc94128bcf6
Missing coverage · 253 benchmark versions

No result does not mean a zero, or that the model was never tested. Collection failures and disputed versions retain their distinct status.

Variants / reasoning settings

Artificial Analysis snapshot 2026-11-03 · Intelligence Index v5.0 (est. = estimated from v4, not measured) · Coding Index v4.x frozen 2026-10-27 · Data: Artificial Analysis · Data: Epoch AI (CC BY)

VariantAA CodingAA Intelligence
Kimi K3 (Max)76.233.4est.
Kimi K3 (Low)72.017.4
Kimi K3——

SUBSCRIPTION PLAN

GitHub Copilot

Current usage-based billing · model token cost is converted to AI Credits at 1 credit = $0.01.

Input $3.00 / 1M
Cached input $0.300 / 1M
Output $15.00 / 1M
Status GA
Token offers by platform · 34 offers (Adjusted $/task)

Click any underlined price to see how it is estimated and where each input comes from. How we calculate adjusted cost.

34 offers within the active global filters, 1 more outside them; “price n/a” means the provider serves the model but publishes no direct token price we could collect — no other channel's price is shown in its place.

OpenRouter (29)

Prices via OpenRouter — what OpenRouter charges for each provider's endpoint, not the provider's own direct price. Source: openrouter.ai/moonshotai/kimi-k3/providers, collected 2026-11-03.

Relace
Wafer
Sail Research
Sail Research
Wafer
Makora
InferenceNet
InferenceNet
ParetoAlpha
Wafer
Chutes
Decart
Morph
InferenceNet
InferenceNet
Phala
DigitalOcean
AkashML
DeepInfra
Parasail
Modal
Together
Fireworks
BaseTen
Moonshot AI
Amazon Bedrock
Fireworks
Fireworks
Fireworks

Chutes (1)

Direct prices from Chutes's own price list. Source: llm.chutes.ai/v1/models, collected 2026-11-03.

Chutes

TensorX (1)

Direct prices from TensorX's own price list. Source: tensorx.ai/pricing/, collected 2026-11-03.

TensorX

Nebius (1)

Direct prices from Nebius's own price list. Source: tokenfactory.nebius.com/models, collected 2026-11-03.

Nebius

Azure AI Foundry (2)

Direct prices from Azure AI Foundry's own price list. Source: prices.azure.com/api/retail/prices, collected 2026-11-03.

Azure AI Foundry
Azure AI Foundry
Kimi K3 (Max) — benchmarks & cost | Benchmark Heaven