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Mistral · model passport

Mistral: Mistral Medium 3.5

mistral-medium-3-5
  • Open weights
  • Modified MIT licence
  • 262,144 context
  • Released 2025-08-14(curated)
9/27axes covered
Overall · LMArena
1,426#105 of 396
Best percentile
79.9IFBench (Artificial Analysis)
Cohort standing
52.8median 51.8

What the data says

Benchmarked on 9 of 27 tracked axes. Every figure below is the model's own published result on that board.

Weakest axes

  • 7.3 pct — Agent Arena (-0.117)

Uneven: 72.6 percentile points between its best and worst axis — 79.9 pct on IFBench (Artificial Analysis) versus 7.3 pct on Agent Arena.

  • IFBench (Artificial Analysis)79.9 pct68.8%Verify →
  • Instruction following75.5 pct1,422Verify →
  • Coding73.9 pct1,478Verify →
  • Overall73.7 pct1,426Verify →
  • Hard prompts72 pct1,445Verify →
  • Vision Arena46.7 pct1,200Verify →
  • Factuality Arena39 pct1,430Verify →
  • WebDev Arena15.1 pct1,264Verify →
  • Agent Arena7.3 pct-0.117Verify →
  • Search ArenaNot benchmarked
  • Document 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
  • MMLU-Pro (Artificial Analysis)Not benchmarked
  • LiveCodeBench (Artificial Analysis)Not benchmarked
  • HHEM Hallucination (Vectara)Not benchmarked
  • SWE-bench VerifiedNot benchmarked
  • Terminal-BenchNot 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-3-5
Context length262,144 tokens
Max output209,715 tokens
Acceptstext, image, file
Input price$1.50 per 1M tokens
Output price$7.50 per 1M tokens

API parameters this endpoint supports

Frequency penaltyInclude reasoningMax tokensPresence penaltyReasoningReasoning effortResponse 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-3-5","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-3.5 stands at 52.8 (raw mean 53.7) — measured on 9 of 27 axes.

    standingtemplateVerify →

  • mistral-medium-3.5 stands at 52.8 versus a cohort median of 51.8 across 146 models released within 180 days — above the peer median.

    cohorttemplateVerify →

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 →