Mistral AI, released May 7, 2025

Mistral Medium 3price, context, benchmarks and release details

Provisional: not enough results to rank yet 85% confidence 85 percent, High confidence, 4 of 7 expected sources in
33.0
SI Score
#136 of 142 ranked models
Input, per 1M tokens
not yet reported
Output, per 1M tokens
not yet reported
Context window
131Kmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
Max output
131Kmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
Released
May 7, 2025models.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗

How the score breaks down

Coding (weight 40 percent) 3.8
Math (weight 15 percent) 65.2
Preference (weight 15 percent) 45.7
Reasoning (weight 30 percent) 22.9

Weights: reasoning 30%, math 15%, coding 40%, preference 15%. Results use fixed 0–100 scales before averaging, and thin evidence is pulled toward 50. Method si-v3-retained-evidence-2, computed Oct 9, 2026, 05:13 UTC.

Around it on the leaderboard

  1. 134 Nova Lite 36.6
  2. 135 Mistral Large 2.1 35.3
  3. 136 Mistral Medium 3 33.0
  4. 137 Llama-3.3-70B-Instruct 32.7
  5. 138 Llama-3.2-1B 32.1

Full leaderboard

Benchmark results

6 benchmarks, 6 results

Each row shows the best published result. Where a model was tested at several settings, such as reasoning effort, open the row to see each one. Hover or tap a value for its source.

GPQA Diamondreasoning 59.5%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published May 7, 2025 Retrieved Oct 9, 2026 · CC-BY
Open source ↗ 59.5
Humanity's Last Exam (Scale AI)reasoning 4.5%Humanity’s Last ExamPotential contamination warning: This model was evaluated after the public release of HLE, allowing model builder access to the prompts and solutions. [variant] Published May 13, 2025 Retrieved Oct 9, 2026 · factual citation
Open source ↗ 4.5
MATH Level 5math 81.6%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published May 7, 2025 Retrieved Oct 9, 2026 · CC-BY
Open source ↗ 81.6
OTIS Mock AIME 2024–2025math 32.2%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published May 7, 2025 Retrieved Oct 9, 2026 · CC-BY
Open source ↗ 32.2
Terminal-Benchcoding 3.8%Official model cards via models.devLab-reported; metric success rate; transcribed by MIT models.dev catalog; not independently evaluated [variant] Published May 30, 2026 Retrieved Oct 9, 2026 · factual citation; MIT transcription
Open source ↗ 3.8
LMArena Textpreference 1165.1 eloLMArena / ArenaPublished source fact [variant] text / overallPublished Oct 8, 2026 Retrieved Oct 9, 2026 · CC-BY-4.0
Open source ↗ 45.7

Normalization uses a fixed 0–100 scale for each unit, independent of other models. Compare evaluation conditions before reading a small gap as decisive. “Lab-reported” marks the provider's own published figure.

Details and sources

Open weights
Nomodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
License
not yet reported
Input modalities
text, imagemodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
First seen by SuperIndex
Oct 8, 2026
Coverage
68% of expected source weight

Reported (4)

  • Epoch AI BenchmarkingOct 8, 2026
  • Humanity’s Last ExamOct 8, 2026
  • Official model cards via models.devOct 8, 2026
  • LMArena / ArenaOct 8, 2026

Awaiting (3)

  • ARC Prize13% of weight
  • LiveBench13% of weight
  • Terminal-Bench6% of weight

Confidence rises as pending sources publish. Some sources never cover some models, so confidence reaches 100% at 80% of expected weight.

What changed

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