Model comparison
GPT-5 Nano vs Mistral Small 3.1
GPT-5 Nano is the stronger model overall, scoring 33.5 to 31.7 on the Noometry Index.
Last verified . 27 shared benchmarks.
Mistral AISummary
- They share 27 benchmarks with published results for both. GPT-5 Nano scores higher in 5 categories and Mistral Small 3.1 in 4 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5 Nano leads 29.4 to 14.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 81.1% for GPT-5 Nano and 3.9% for Mistral Small 3.1.
- GPT-5 Nano is cheaper at $0.05 / $0.40 per million input/output tokens, against $0.35 / $0.56 for Mistral Small 3.1.
- GPT-5 Nano accepts more context: 400K tokens versus 128K.
- Mistral Small 3.1 has downloadable open weights; the other is API-only.
Side by side
| GPT-5 Nano | Mistral Small 3.1 | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 33.5 | 31.7 |
| Released | 2025-08-07 | 2025-03-17 |
| Weights | Proprietary | Open |
| Context window | 400K | 128K |
| Max output | 128K | 102K |
| Input $ / M tokens | $0.05 | $0.35 |
| Output $ / M tokens | $0.40 | $0.56 |
| Results tracked | 49 | 28 |
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Category by category
Coding Mistral Small 3.1 leads
GPT-5 Nano: 33.6 (#254), Mistral Small 3.1: 38.3 (#179)
| Benchmark | GPT-5 Nano | Mistral Small 3.1 |
|---|---|---|
| LMArena Coding | 1351 | 1309 |
| SWE-bench Verified (bash only) | 34.8% | — |
| WeirdML | 38.1% | — |
| ALE-Bench | 718.67 | — |
Agentic & Tool Use Not comparable
GPT-5 Nano: 25.8 (#106), Mistral Small 3.1: —
| Benchmark | GPT-5 Nano | Mistral Small 3.1 |
|---|---|---|
| Terminal-Bench | 21.8% | — |
| Berkeley Function Calling Leaderboard | 51.5% | — |
Reasoning Mistral Small 3.1 leads
GPT-5 Nano: 16.3 (#306), Mistral Small 3.1: 19.7 (#254)
| Benchmark | GPT-5 Nano | Mistral Small 3.1 |
|---|---|---|
| Chess Puzzles | 27% | 1% |
| LMArena Hard Prompts | 1328 | 1278 |
| Epoch Capabilities Index | 139.38 | 127.48 |
| ARC-AGI-2 | 2.6% | — |
| Kagi LLM Benchmark | 62.2% | — |
| ARC-AGI-1 | 20.7% | — |
| Mystery Game Puzzles | 9% | — |
| DTBench | 62.7% | — |
| LMCA | 7.9% | — |
| ForecastBench | 59.1 | — |
Math GPT-5 Nano leads
GPT-5 Nano: 29.4 (#241), Mistral Small 3.1: 14.7 (#301)
| Benchmark | GPT-5 Nano | Mistral Small 3.1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 81.1% | 3.9% |
| Omni-MATH | 54.6% | 24.8% |
| LMArena Math | 1317 | 1262 |
| FrontierMath (Tiers 1-3) | 20% | — |
| FrontierMath Tier 4 | 2.4% | — |
| ProofBench | 12% | — |
| MATH Level 5 | 95.2% | — |
| FrontierMath (Feb 2025 set) | 8.3% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge GPT-5 Nano leads
GPT-5 Nano: 35.9 (#178), Mistral Small 3.1: 22.6 (#271)
| Benchmark | GPT-5 Nano | Mistral Small 3.1 |
|---|---|---|
| GPQA Diamond | 69.4% | 41.9% |
| MMLU-Pro | 77.8% | 61% |
| GPQA (HELM) | 67.9% | 39.2% |
| LMArena Expert | 1321 | 1257 |
| SimpleQA Verified | 11.7% | — |
| Vectara Hallucination Rate | 10.5% | — |
Multimodal Mistral Small 3.1 leads
GPT-5 Nano: 31.3 (#108), Mistral Small 3.1: 33.2 (#99)
| Benchmark | GPT-5 Nano | Mistral Small 3.1 |
|---|---|---|
| LMArena Vision | 1159 | 1136 |
| VPCT | 37.2% | — |
Multilingual GPT-5 Nano leads
GPT-5 Nano: 45.3 (#172), Mistral Small 3.1: 41.2 (#209)
| Benchmark | GPT-5 Nano | Mistral Small 3.1 |
|---|---|---|
| LMArena Non-English | 1313 | 1255 |
| LMArena Chinese | 1356 | 1253 |
| LMArena German | 1327 | 1266 |
| LMArena Japanese | 1226 | 1208 |
| LMArena Korean | 1269 | 1206 |
| LMArena Russian | 1296 | 1263 |
| LMArena Spanish | 1360 | 1283 |
| LMArena French | — | 1273 |
Instruction Following GPT-5 Nano leads
GPT-5 Nano: 75.0 (#79), Mistral Small 3.1: 63.6 (#230)
| Benchmark | GPT-5 Nano | Mistral Small 3.1 |
|---|---|---|
| IFEval | 93.2% | 75% |
| LMArena Instruction Following | 1306 | 1264 |
Long Context Mistral Small 3.1 leads
GPT-5 Nano: 31.3 (#281), Mistral Small 3.1: 39.5 (#178)
| Benchmark | GPT-5 Nano | Mistral Small 3.1 |
|---|---|---|
| LMArena Longer Query | 1312 | 1299 |
| Fiction.LiveBench | 44.4% | — |
Writing & Preference GPT-5 Nano leads
GPT-5 Nano: 39.1 (#249), Mistral Small 3.1: 37.0 (#259)
| Benchmark | GPT-5 Nano | Mistral Small 3.1 |
|---|---|---|
| LMArena Text | 1320 | 1277 |
| LMArena Creative Writing | 1249 | 1253 |
| EQ-Bench Creative Writing | 705 | 761 |
| WildBench | 80.6% | 78.8% |
| LMArena Multi-Turn | 1311 | 1270 |
Frequently asked questions
Is GPT-5 Nano better than Mistral Small 3.1?
GPT-5 Nano is the stronger model overall, scoring 33.5 to 31.7 on the Noometry Index.
Which is cheaper, GPT-5 Nano or Mistral Small 3.1?
GPT-5 Nano is cheaper. It lists at $0.05 per million input tokens and $0.40 per million output tokens; Mistral Small 3.1 lists at $0.35 and $0.56.
Is GPT-5 Nano or Mistral Small 3.1 better for coding?
Mistral Small 3.1 scores higher on coding benchmarks: 38.3 versus 33.6 in the Noometry coding category.
Which has the bigger context window?
GPT-5 Nano does, with 400K tokens against 128K.
How many benchmarks do GPT-5 Nano and Mistral Small 3.1 share?
27 benchmarks have published results for both models. GPT-5 Nano has 49 scored results on Noometry and Mistral Small 3.1 has 28.