Model comparison
GPT-5.1 vs Mistral Medium
GPT-5.1 is the stronger model overall, scoring 49.0 to 36.3 on the Noometry Index.
Last verified . 29 shared benchmarks.
Mistral AISummary
- They share 29 benchmarks with published results for both. GPT-5.1 scores higher in 10 categories and Mistral Medium in 0 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GPT-5.1 leads 50.6 to 25.0.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 88.6% for GPT-5.1 and 32.2% for Mistral Medium.
- Mistral Medium is cheaper at $1.50 / $7.50 per million input/output tokens, against $1.25 / $10 for GPT-5.1.
- GPT-5.1 accepts more context: 400K tokens versus 262K.
- Mistral Medium has downloadable open weights; the other is API-only.
Side by side
| GPT-5.1 | Mistral Medium | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 49.0 | 36.3 |
| Released | 2025-11-13 | 2023-12-11 |
| Weights | Proprietary | Open |
| Context window | 400K | 262K |
| Max output | 128K | 262K |
| Input $ / M tokens | $1.25 | $1.50 |
| Output $ / M tokens | $10 | $7.50 |
| Results tracked | 63 | 36 |
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Category by category
Coding GPT-5.1 leads
GPT-5.1: 46.4 (#66), Mistral Medium: 34.2 (#243)
| Benchmark | GPT-5.1 | Mistral Medium |
|---|---|---|
| SciCode | 43.3% | 40.2% |
| WeirdML | 60.8% | 43.7% |
| LMArena Coding | 1454 | 1434 |
| ALE-Bench | 1,192 | 763.98 |
| SWE-bench Verified | 68% | — |
| FrontierCode | — | 8% |
| SWE-bench Verified (bash only) | 66% | — |
| LMArena WebDev | 1395 | — |
| GSO | 13.7% | — |
| LiveBench Coding | 72.5% | — |
Agentic & Tool Use GPT-5.1 leads
GPT-5.1: 32.7 (#60), Mistral Medium: 28.3 (#90)
| Benchmark | GPT-5.1 | Mistral Medium |
|---|---|---|
| Terminal-Bench | 47.6% | — |
| Berkeley Function Calling Leaderboard | — | 37.7% |
| DeepResearch Bench | 42.8% | — |
| LMArena Search | 1199 | — |
| Vending-Bench 2 | 1,473 | — |
Reasoning GPT-5.1 leads
GPT-5.1: 39.8 (#58), Mistral Medium: 24.0 (#167)
| Benchmark | GPT-5.1 | Mistral Medium |
|---|---|---|
| CritPt | 4.9% | 0% |
| LMArena Hard Prompts | 1457 | 1426 |
| DTBench | 90.1% | 75.5% |
| LMCA | 43.9% | 26.1% |
| ARC-AGI-2 | 17.6% | — |
| SimpleBench | 53.2% | — |
| Kagi LLM Benchmark | — | 50% |
| ARC-AGI-1 | 72.8% | — |
| Chess Puzzles | 32% | — |
| EnigmaEval | 11.2% | — |
| LiveBench Reasoning | 95.8% | — |
| Mystery Game Puzzles | 19% | — |
| LiveBench Data Analysis | 72.1% | — |
| Surface Evolver Bench | — | 26.9% |
| Epoch Capabilities Index | 149.64 | — |
| ForecastBench | 58.1 | — |
| LiveBench | 78.8% | — |
Math GPT-5.1 leads
GPT-5.1: 52.2 (#51), Mistral Medium: 28.1 (#245)
| Benchmark | GPT-5.1 | Mistral Medium |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 88.6% | 32.2% |
| LMArena Math | 1447 | 1408 |
| FrontierMath (Feb 2025 set) | 31% | 0.3% |
| ProofBench | — | 9% |
| Omni-MATH | 46.4% | — |
| LiveBench Math | 94.5% | — |
| MATH Level 5 | — | 81.6% |
| FrontierMath Tier 4 (v1) | 12.5% | — |
Knowledge GPT-5.1 leads
GPT-5.1: 50.6 (#71), Mistral Medium: 25.0 (#265)
| Benchmark | GPT-5.1 | Mistral Medium |
|---|---|---|
| GPQA Diamond | 87.6% | 59.5% |
| Humanity's Last Exam | 23.7% | 4.5% |
| Vectara Hallucination Rate | 10.9% | 22.7% |
| LMArena Expert | 1470 | 1408 |
| SimpleQA Verified | 48% | — |
| MMLU-Pro | 57.9% | — |
| GPQA (HELM) | 44.2% | — |
Multimodal GPT-5.1 leads
GPT-5.1: 44.8 (#19), Mistral Medium: 35.3 (#88)
| Benchmark | GPT-5.1 | Mistral Medium |
|---|---|---|
| LMArena Vision | 1250 | 1172 |
| VPCT | 58.7% | — |
| LMArena Document | 1403 | — |
Multilingual GPT-5.1 leads
GPT-5.1: 53.8 (#56), Mistral Medium: 52.1 (#91)
| Benchmark | GPT-5.1 | Mistral Medium |
|---|---|---|
| LMArena Non-English | 1431 | 1408 |
| LMArena Chinese | 1495 | 1447 |
| LMArena French | 1450 | 1459 |
| LMArena German | 1438 | 1432 |
| LMArena Japanese | 1453 | 1378 |
| LMArena Korean | 1401 | 1380 |
| LMArena Russian | 1435 | 1411 |
| LMArena Spanish | 1433 | 1433 |
Instruction Following GPT-5.1 leads
GPT-5.1: 83.9 (#1), Mistral Medium: 73.7 (#116)
| Benchmark | GPT-5.1 | Mistral Medium |
|---|---|---|
| LMArena Instruction Following | 1443 | 1398 |
| LiveBench Instruction Following | 93.3% | — |
| IFEval | 93.5% | — |
Long Context GPT-5.1 leads
GPT-5.1: 47.6 (#14), Mistral Medium: 42.9 (#114)
| Benchmark | GPT-5.1 | Mistral Medium |
|---|---|---|
| LMArena Longer Query | 1447 | 1406 |
| CL-bench | 23.7% | — |
| CL-bench Life | 17.3% | — |
Writing & Preference GPT-5.1 leads
GPT-5.1: 64.5 (#55), Mistral Medium: 60.0 (#103)
| Benchmark | GPT-5.1 | Mistral Medium |
|---|---|---|
| LMArena Text | 1443 | 1424 |
| LMArena Creative Writing | 1427 | 1391 |
| LMArena Multi-Turn | 1450 | 1418 |
| Short-Story Creative Writing | — | 77.3% |
| WildBench | 86.3% | — |
| LiveBench Language | 80.2% | — |
Frequently asked questions
Is GPT-5.1 better than Mistral Medium?
GPT-5.1 is the stronger model overall, scoring 49.0 to 36.3 on the Noometry Index.
Which is cheaper, GPT-5.1 or Mistral Medium?
Mistral Medium is cheaper. It lists at $1.50 per million input tokens and $7.50 per million output tokens; GPT-5.1 lists at $1.25 and $10.
Is GPT-5.1 or Mistral Medium better for coding?
GPT-5.1 scores higher on coding benchmarks: 46.4 versus 34.2 in the Noometry coding category.
Which has the bigger context window?
GPT-5.1 does, with 400K tokens against 262K.
How many benchmarks do GPT-5.1 and Mistral Medium share?
29 benchmarks have published results for both models. GPT-5.1 has 63 scored results on Noometry and Mistral Medium has 36.