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aiqbench

Mistral · model passport

Mistral: Mistral Medium 3.1

mistral-medium-3-1
  • 131,072 context
3/27axes covered
Best percentile
50.4LiveCodeBench (Artificial Analysis)
Composite standing
46.3shrunk · 3/27 axes

What the data says

Benchmarked on 3 of 27 tracked axes. Every figure below is the model's own published result on that board.

Uneven: 13.7 percentile points between its best and worst axis — 50.4 pct on LiveCodeBench (Artificial Analysis) versus 36.7 pct on MMLU-Pro (Artificial Analysis).

  • LiveCodeBench (Artificial Analysis)50.4 pct40.6%Verify →
  • IFBench (Artificial Analysis)40.7 pct39.8%Verify →
  • MMLU-Pro (Artificial Analysis)36.7 pct68.3%Verify →
  • OverallNot benchmarked
  • WebDev ArenaNot benchmarked
  • Vision ArenaNot benchmarked
  • Factuality ArenaNot benchmarked
  • Search ArenaNot benchmarked
  • Document ArenaNot benchmarked
  • Agent ArenaNot benchmarked
  • GPQA DiamondNot benchmarked
  • AIME (math)Not benchmarked
  • FrontierMathNot benchmarked
  • SimpleQA VerifiedNot benchmarked
  • ARC-AGI-2Not benchmarked
  • Humanity's Last ExamNot benchmarked
  • SimpleBenchNot benchmarked
  • LiveBenchNot benchmarked
  • BFCL v4 (function calling)Not benchmarked
  • SWE-bench Verified (live board)Not benchmarked
  • Terminal-Bench 4.0Not benchmarked
  • HHEM Hallucination (Vectara)Not benchmarked
  • SWE-bench VerifiedNot benchmarked
  • Terminal-BenchNot benchmarked
  • CodingNot benchmarked
  • Instruction followingNot benchmarked
  • Hard promptsNot benchmarked

Percentiles are the model's standing within each board's own population. Axes marked "not benchmarked" have no published result for this model — that is an absence of data, not a low score.

How to run it

Use it hosted

API model IDmistralai/mistral-medium-3.1
Context length131,072 tokens
Max output104,857 tokens
Acceptstext, image, file
Input price$0.40 per 1M tokens
Cached input price$0.04 per 1M tokens
Output price$2 per 1M tokens

API parameters this endpoint supports

Frequency penaltyMax tokensPresence penaltyResponse formatSeedStop sequencesStructured outputsTemperatureTool choiceTool callingTop-p

Example request

curl https://openrouter.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"mistralai/mistral-medium-3.1","messages":[{"role":"user","content":"Hello"}]}'

View on OpenRouter →

Identifiers, limits and prices are synced from the upstream source shown above. Any field we haven't synced is left out entirely rather than guessed.

  • Mistral Medium 3.1 stands at 46.3 (raw mean 42.6) — measured on 3 of 27 axes.

    standingtemplateVerify →

Every claim is a computed fact from the current board data, phrased by a low-temperature model call and rejected by a validation gate if any number is not in the source row. How the leaderboards work →