Model comparison
GPT-5 Nano vs Mistral Medium 3.1
GPT-5 Nano is the stronger model overall, scoring 33.4 to 31.5 on the Noometry Index.
Last verified . 1 shared benchmarks.
Mistral AISummary
- They share 1 benchmark with published results for both. GPT-5 Nano scores higher in 1 category and Mistral Medium 3.1 in 1 category; 2 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Mistral Medium 3.1 leads 55.6 to 39.4.
- GPT-5 Nano is cheaper at $0.05 / $0.40 per million input/output tokens, against $0.40 / $2 for Mistral Medium 3.1.
- GPT-5 Nano accepts more context: 400K tokens versus 131K.
Side by side
| GPT-5 Nano | Mistral Medium 3.1 | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 33.4 | 31.5 |
| Released | 2025-08-07 | — |
| Weights | Proprietary | Proprietary |
| Context window | 400K | 131K |
| Max output | 128K | 105K |
| Input $ / M tokens | $0.05 | $0.40 |
| Output $ / M tokens | $0.40 | $2 |
| Results tracked | 48 | 3 |
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Category by category
Coding Not comparable
GPT-5 Nano: 33.3 (#248), Mistral Medium 3.1: —
| Benchmark | GPT-5 Nano | Mistral Medium 3.1 |
|---|---|---|
| SWE-bench Verified (bash only) | 34.8% | — |
| WeirdML | 38.1% | — |
| LMArena Coding | 1351 | — |
| ALE-Bench | 718.67 | — |
Agentic & Tool Use Not comparable
GPT-5 Nano: 25.6 (#99), Mistral Medium 3.1: —
| Benchmark | GPT-5 Nano | Mistral Medium 3.1 |
|---|---|---|
| Terminal-Bench | 21.8% | — |
| Berkeley Function Calling Leaderboard | 51.5% | — |
Reasoning GPT-5 Nano leads
GPT-5 Nano: 16.4 (#291), Mistral Medium 3.1: 10.1 (#336)
| Benchmark | GPT-5 Nano | Mistral Medium 3.1 |
|---|---|---|
| ARC-AGI-2 | 2.6% | — |
| Kagi LLM Benchmark | 62.2% | — |
| NYT Connections (extended) | — | 6.5% |
| ARC-AGI-1 | 20.7% | — |
| Chess Puzzles | 27% | — |
| Thematic Generalization | — | 20.3% |
| LMArena Hard Prompts | 1329 | — |
| Mystery Game Puzzles | 9% | — |
| DTBench | 62.7% | — |
| LMCA | 7.9% | — |
| Epoch Capabilities Index | 139.39 | — |
| ForecastBench | 59.1 | — |
Math Not comparable
GPT-5 Nano: 29.1 (#221), Mistral Medium 3.1: —
| Benchmark | GPT-5 Nano | Mistral Medium 3.1 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 20% | — |
| FrontierMath Tier 4 | 2.4% | — |
| OTIS Mock AIME 2024-2025 | 81.1% | — |
| ProofBench | 12% | — |
| Omni-MATH | 54.6% | — |
| LMArena Math | 1318 | — |
| MATH Level 5 | 95.2% | — |
| FrontierMath (Feb 2025 set) | 8.3% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge Not comparable
GPT-5 Nano: 35.8 (#166), Mistral Medium 3.1: —
| Benchmark | GPT-5 Nano | Mistral Medium 3.1 |
|---|---|---|
| GPQA Diamond | 69.4% | — |
| SimpleQA Verified | 11.7% | — |
| MMLU-Pro | 77.8% | — |
| Vectara Hallucination Rate | 10.5% | — |
| GPQA (HELM) | 67.9% | — |
| LMArena Expert | 1321 | — |
Multimodal Not comparable
GPT-5 Nano: 30.7 (#102), Mistral Medium 3.1: —
| Benchmark | GPT-5 Nano | Mistral Medium 3.1 |
|---|---|---|
| LMArena Vision | 1159 | — |
| VPCT | 37.2% | — |
Multilingual Not comparable
GPT-5 Nano: 45.5 (#167), Mistral Medium 3.1: —
| Benchmark | GPT-5 Nano | Mistral Medium 3.1 |
|---|---|---|
| LMArena Non-English | 1313 | — |
| LMArena Chinese | 1355 | — |
| LMArena German | 1329 | — |
| LMArena Korean | 1269 | — |
| LMArena Russian | 1296 | — |
| LMArena Spanish | 1360 | — |
Instruction Following Not comparable
GPT-5 Nano: 75.2 (#72), Mistral Medium 3.1: —
| Benchmark | GPT-5 Nano | Mistral Medium 3.1 |
|---|---|---|
| IFEval | 93.2% | — |
| LMArena Instruction Following | 1306 | — |
Long Context Not comparable
GPT-5 Nano: 31.3 (#275), Mistral Medium 3.1: —
| Benchmark | GPT-5 Nano | Mistral Medium 3.1 |
|---|---|---|
| Fiction.LiveBench | 44.4% | — |
| LMArena Longer Query | 1313 | — |
Writing & Preference Mistral Medium 3.1 leads
GPT-5 Nano: 39.4 (#244), Mistral Medium 3.1: 55.6 (#140)
| Benchmark | GPT-5 Nano | Mistral Medium 3.1 |
|---|---|---|
| EQ-Bench Creative Writing | 705 | 1476 |
| LMArena Text | 1320 | — |
| LMArena Creative Writing | 1250 | — |
| WildBench | 80.6% | — |
| LMArena Multi-Turn | 1311 | — |
Frequently asked questions
Is GPT-5 Nano better than Mistral Medium 3.1?
GPT-5 Nano is the stronger model overall, scoring 33.4 to 31.5 on the Noometry Index.
Which is cheaper, GPT-5 Nano or Mistral Medium 3.1?
GPT-5 Nano is cheaper. It lists at $0.05 per million input tokens and $0.40 per million output tokens; Mistral Medium 3.1 lists at $0.40 and $2.
Which has the bigger context window?
GPT-5 Nano does, with 400K tokens against 131K.
How many benchmarks do GPT-5 Nano and Mistral Medium 3.1 share?
1 benchmark has published results for both models. GPT-5 Nano has 48 scored results on Noometry and Mistral Medium 3.1 has 3.