Mistral Medium 3: Price, Context, Benchmarks, and Release Details
33.0
SI Score (method si-v2-absolute-shrinkage-1)
#113 of 115 ranked
85% confidence 85 percent, High confidence — 4 of 7 expected sources in
Coverage 68% of expected source weight · 100% confidence at 80% coverage
Pillar breakdown
Coding (weight 40 percent) 3.8
Math (weight 15 percent) 65.2
Preference (weight 15 percent) 45.6
Reasoning (weight 30 percent) 22.9
Pillar weights: reasoning 30% · math 15% · coding 40% · preference 15%. Benchmark results use fixed 0–100 scales before averaging; incomplete evidence is shrunk toward 50.
Facts
- Input price / 1M
- not yet reported
- Output price / 1M
- not yet reported
- Context window
- 131Kmodels.devPublished source fact
Retrieved Oct 8, 2026 · MIT
Open source ↗ - Max output
- 131Kmodels.devPublished source fact
Retrieved Oct 8, 2026 · MIT
Open source ↗ - Released
- May 7, 2025models.devPublished source fact
Retrieved Oct 8, 2026 · MIT
Open source ↗ - Open weights
- Nomodels.devPublished source fact
Retrieved Oct 8, 2026 · MIT
Open source ↗ - License
- not yet reported
- Input modalities
- text, imagemodels.devPublished source fact
Retrieved Oct 8, 2026 · MIT
Open source ↗
Benchmark results
6 results| Benchmark | Raw result | Normalized (0–100) | Pillar |
|---|---|---|---|
| gpqa diamond | 59.5%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published May 7, 2025
Retrieved Oct 8, 2026 · CC-BY Open source ↗ | 59.5 | reasoning |
| hle scale | 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 8, 2026 · factual citation Open source ↗ | 4.5 | reasoning |
| lmarena text | 1165.1 eloLMArena / ArenaPublished source fact [variant] text / overallPublished Oct 2, 2026
Retrieved Oct 8, 2026 · CC-BY-4.0 Open source ↗ | 45.6 | preference |
| math level 5 | 81.6%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published May 7, 2025
Retrieved Oct 8, 2026 · CC-BY Open source ↗ | 81.6 | math |
| otis mock aime 2024 2025 | 32.2%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published May 7, 2025
Retrieved Oct 8, 2026 · CC-BY Open source ↗ | 32.2 | math |
| terminal bench | 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 8, 2026 · factual citation; MIT transcription Open source ↗ | 3.8 | coding |
Normalization uses fixed absolute 0–100 scales for each unit, independently of other models that have a result on each benchmark. Coverage and evidence breadth still affect the composite; compare the evaluation conditions before reading a small score gap as decisive. “lab-reported” marks the provider's own published figure.
Sources: in and pending
in Reported (4)
- Epoch AI Benchmarking · arrived Oct 8, 2026
- Humanity’s Last Exam · arrived Oct 8, 2026
- Official model cards via models.dev · arrived Oct 8, 2026
- LMArena / Arena · arrived Oct 8, 2026
pending Awaiting (3)
- ARC Prize · carries 13% of expected weight
- LiveBench · carries 13% of expected weight
- Terminal-Bench · carries 6% of expected weight
The confidence % rises as pending sources publish. Some sources never cover some models — that is why 100% confidence arrives at 80% of expected weight, not at full coverage.