Model comparison
GPT-5.1 vs Mistral Small 3.1
GPT-5.1 is the stronger model overall, scoring 49.0 to 31.7 on the Noometry Index. Mistral Small 3.1 costs 8.6× less per token, which makes it the better buy when GPT-5.1's lead doesn't matter for your workload.
Last verified . 27 shared benchmarks.
Summary
- They share 27 benchmarks with published results for both. GPT-5.1 scores higher in 9 categories and Mistral Small 3.1 in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.1 leads 52.2 to 14.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 88.6% for GPT-5.1 and 3.9% for Mistral Small 3.1.
- Mistral Small 3.1 is cheaper at $0.35 / $0.56 per million input/output tokens, against $1.25 / $10 for GPT-5.1.
- GPT-5.1 accepts more context: 400K tokens versus 128K.
- Mistral Small 3.1 has downloadable open weights; the other is API-only.
Side by side
| GPT-5.1 | Mistral Small 3.1 | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 49.0 | 31.7 |
| Released | 2025-11-13 | 2025-03-17 |
| Weights | Proprietary | Open |
| Context window | 400K | 128K |
| Max output | 128K | 102K |
| Input $ / M tokens | $1.25 | $0.35 |
| Output $ / M tokens | $10 | $0.56 |
| Results tracked | 63 | 28 |
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Category by category
Coding GPT-5.1 leads
GPT-5.1: 46.4 (#66), Mistral Small 3.1: 38.3 (#179)
| Benchmark | GPT-5.1 | Mistral Small 3.1 |
|---|---|---|
| LMArena Coding | 1454 | 1309 |
| SWE-bench Verified | 68% | — |
| SWE-bench Verified (bash only) | 66% | — |
| LMArena WebDev | 1395 | — |
| SciCode | 43.3% | — |
| GSO | 13.7% | — |
| WeirdML | 60.8% | — |
| LiveBench Coding | 72.5% | — |
| ALE-Bench | 1,192 | — |
Agentic & Tool Use Not comparable
GPT-5.1: 32.7 (#60), Mistral Small 3.1: —
| Benchmark | GPT-5.1 | Mistral Small 3.1 |
|---|---|---|
| Terminal-Bench | 47.6% | — |
| DeepResearch Bench | 42.8% | — |
| LMArena Search | 1199 | — |
| Vending-Bench 2 | 1,473 | — |
Reasoning GPT-5.1 leads
GPT-5.1: 39.8 (#58), Mistral Small 3.1: 19.7 (#254)
| Benchmark | GPT-5.1 | Mistral Small 3.1 |
|---|---|---|
| Chess Puzzles | 32% | 1% |
| LMArena Hard Prompts | 1457 | 1278 |
| Epoch Capabilities Index | 149.64 | 127.48 |
| ARC-AGI-2 | 17.6% | — |
| SimpleBench | 53.2% | — |
| ARC-AGI-1 | 72.8% | — |
| CritPt | 4.9% | — |
| EnigmaEval | 11.2% | — |
| LiveBench Reasoning | 95.8% | — |
| Mystery Game Puzzles | 19% | — |
| DTBench | 90.1% | — |
| LiveBench Data Analysis | 72.1% | — |
| LMCA | 43.9% | — |
| ForecastBench | 58.1 | — |
| LiveBench | 78.8% | — |
Math GPT-5.1 leads
GPT-5.1: 52.2 (#51), Mistral Small 3.1: 14.7 (#301)
| Benchmark | GPT-5.1 | Mistral Small 3.1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 88.6% | 3.9% |
| Omni-MATH | 46.4% | 24.8% |
| LMArena Math | 1447 | 1262 |
| LiveBench Math | 94.5% | — |
| FrontierMath (Feb 2025 set) | 31% | — |
| FrontierMath Tier 4 (v1) | 12.5% | — |
Knowledge GPT-5.1 leads
GPT-5.1: 50.6 (#71), Mistral Small 3.1: 22.6 (#271)
| Benchmark | GPT-5.1 | Mistral Small 3.1 |
|---|---|---|
| GPQA Diamond | 87.6% | 41.9% |
| MMLU-Pro | 57.9% | 61% |
| GPQA (HELM) | 44.2% | 39.2% |
| LMArena Expert | 1470 | 1257 |
| Humanity's Last Exam | 23.7% | — |
| SimpleQA Verified | 48% | — |
| Vectara Hallucination Rate | 10.9% | — |
Multimodal GPT-5.1 leads
GPT-5.1: 44.8 (#19), Mistral Small 3.1: 33.2 (#99)
| Benchmark | GPT-5.1 | Mistral Small 3.1 |
|---|---|---|
| LMArena Vision | 1250 | 1136 |
| VPCT | 58.7% | — |
| LMArena Document | 1403 | — |
Multilingual GPT-5.1 leads
GPT-5.1: 53.8 (#56), Mistral Small 3.1: 41.2 (#209)
| Benchmark | GPT-5.1 | Mistral Small 3.1 |
|---|---|---|
| LMArena Non-English | 1431 | 1255 |
| LMArena Chinese | 1495 | 1253 |
| LMArena French | 1450 | 1273 |
| LMArena German | 1438 | 1266 |
| LMArena Japanese | 1453 | 1208 |
| LMArena Korean | 1401 | 1206 |
| LMArena Russian | 1435 | 1263 |
| LMArena Spanish | 1433 | 1283 |
Instruction Following GPT-5.1 leads
GPT-5.1: 83.9 (#1), Mistral Small 3.1: 63.6 (#230)
| Benchmark | GPT-5.1 | Mistral Small 3.1 |
|---|---|---|
| IFEval | 93.5% | 75% |
| LMArena Instruction Following | 1443 | 1264 |
| LiveBench Instruction Following | 93.3% | — |
Long Context GPT-5.1 leads
GPT-5.1: 47.6 (#14), Mistral Small 3.1: 39.5 (#178)
| Benchmark | GPT-5.1 | Mistral Small 3.1 |
|---|---|---|
| LMArena Longer Query | 1447 | 1299 |
| CL-bench | 23.7% | — |
| CL-bench Life | 17.3% | — |
Writing & Preference GPT-5.1 leads
GPT-5.1: 64.5 (#55), Mistral Small 3.1: 37.0 (#259)
| Benchmark | GPT-5.1 | Mistral Small 3.1 |
|---|---|---|
| LMArena Text | 1443 | 1277 |
| LMArena Creative Writing | 1427 | 1253 |
| WildBench | 86.3% | 78.8% |
| LMArena Multi-Turn | 1450 | 1270 |
| EQ-Bench Creative Writing | — | 761 |
| LiveBench Language | 80.2% | — |
Frequently asked questions
Is GPT-5.1 better than Mistral Small 3.1?
GPT-5.1 is the stronger model overall, scoring 49.0 to 31.7 on the Noometry Index. Mistral Small 3.1 costs 8.6× less per token, which makes it the better buy when GPT-5.1's lead doesn't matter for your workload.
Which is cheaper, GPT-5.1 or Mistral Small 3.1?
Mistral Small 3.1 is cheaper. It lists at $0.35 per million input tokens and $0.56 per million output tokens; GPT-5.1 lists at $1.25 and $10.
Is GPT-5.1 or Mistral Small 3.1 better for coding?
GPT-5.1 scores higher on coding benchmarks: 46.4 versus 38.3 in the Noometry coding category.
Which has the bigger context window?
GPT-5.1 does, with 400K tokens against 128K.
How many benchmarks do GPT-5.1 and Mistral Small 3.1 share?
27 benchmarks have published results for both models. GPT-5.1 has 63 scored results on Noometry and Mistral Small 3.1 has 28.