Model comparison
Mistral Small 3.1 vs o3-mini
o3-mini is the stronger model overall, scoring 36.7 to 31.7 on the Noometry Index. Mistral Small 3.1 costs 4.8× less per token, which makes it the better buy when o3-mini's lead doesn't matter for your workload.
Last verified . 21 shared benchmarks.
Mistral AISummary
- They share 21 benchmarks with published results for both. Mistral Small 3.1 scores higher in 2 categories and o3-mini in 6 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where o3-mini leads 38.3 to 22.6.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 3.9% for Mistral Small 3.1 and 76.9% for o3-mini.
- Mistral Small 3.1 is cheaper at $0.35 / $0.56 per million input/output tokens, against $1.10 / $4.40 for o3-mini.
- o3-mini accepts more context: 200K tokens versus 128K.
- Mistral Small 3.1 has downloadable open weights; the other is API-only.
Side by side
| Mistral Small 3.1 | o3-mini | |
|---|---|---|
| Provider | Mistral AI | OpenAI |
| Noometry Index | 31.7 | 36.7 |
| Released | 2025-03-17 | 2024-12-20 |
| Weights | Open | Proprietary |
| Context window | 128K | 200K |
| Max output | 102K | 100K |
| Input $ / M tokens | $0.35 | $1.10 |
| Output $ / M tokens | $0.56 | $4.40 |
| Results tracked | 28 | 51 |
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Category by category
Coding o3-mini leads
Mistral Small 3.1: 38.3 (#179), o3-mini: 40.8 (#132)
| Benchmark | Mistral Small 3.1 | o3-mini |
|---|---|---|
| LMArena Coding | 1309 | 1378 |
| Aider Polyglot | — | 60.4% |
| SciCode | — | 39.8% |
| GSO | — | 1.3% |
| WeirdML | — | 43.7% |
| LiveBench Coding | — | 82.7% |
| CadEval | — | 54% |
Agentic & Tool Use Not comparable
Mistral Small 3.1: —, o3-mini: 29.6 (#84)
| Benchmark | Mistral Small 3.1 | o3-mini |
|---|---|---|
| Cybench | — | 22.5% |
Reasoning Mistral Small 3.1 leads
Mistral Small 3.1: 19.7 (#254), o3-mini: 16.3 (#305)
| Benchmark | Mistral Small 3.1 | o3-mini |
|---|---|---|
| Chess Puzzles | 1% | 17% |
| LMArena Hard Prompts | 1278 | 1366 |
| Epoch Capabilities Index | 127.48 | 140.34 |
| ARC-AGI-2 | — | 3% |
| SimpleBench | — | 22.8% |
| ARC-AGI-1 | — | 34.5% |
| CritPt | — | 0.3% |
| LiveBench Reasoning | — | 89.6% |
| Mystery Game Puzzles | — | 7% |
| DTBench | — | 68.8% |
| LiveBench Data Analysis | — | 70.6% |
| LMCA | — | 19% |
| ForecastBench | — | 59.6 |
| LiveBench | — | 75.9% |
Math o3-mini leads
Mistral Small 3.1: 14.7 (#301), o3-mini: 28.1 (#244)
| Benchmark | Mistral Small 3.1 | o3-mini |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 3.9% | 76.9% |
| LMArena Math | 1262 | 1396 |
| FrontierMath (Tiers 1-3) | — | 18.6% |
| FrontierMath Tier 4 | — | 0% |
| Omni-MATH | 24.8% | — |
| LiveBench Math | — | 77.3% |
| MATH Level 5 | — | 96.5% |
| FrontierMath (Feb 2025 set) | — | 12.4% |
| FrontierMath Tier 4 (v1) | — | 4.2% |
Knowledge o3-mini leads
Mistral Small 3.1: 22.6 (#271), o3-mini: 38.3 (#146)
| Benchmark | Mistral Small 3.1 | o3-mini |
|---|---|---|
| GPQA Diamond | 41.9% | 77% |
| LMArena Expert | 1257 | 1364 |
| SimpleQA Verified | — | 15.3% |
| MMLU-Pro | 61% | — |
| Confabulations | — | 17.9% |
| GPQA (HELM) | 39.2% | — |
Multimodal Not comparable
Mistral Small 3.1: 33.2 (#99), o3-mini: —
| Benchmark | Mistral Small 3.1 | o3-mini |
|---|---|---|
| LMArena Vision | 1136 | — |
Multilingual o3-mini leads
Mistral Small 3.1: 41.2 (#209), o3-mini: 45.7 (#164)
| Benchmark | Mistral Small 3.1 | o3-mini |
|---|---|---|
| LMArena Non-English | 1255 | 1319 |
| LMArena Chinese | 1253 | 1379 |
| LMArena French | 1273 | 1334 |
| LMArena German | 1266 | 1303 |
| LMArena Japanese | 1208 | 1286 |
| LMArena Korean | 1206 | 1314 |
| LMArena Russian | 1263 | 1304 |
| LMArena Spanish | 1283 | 1321 |
Instruction Following o3-mini leads
Mistral Small 3.1: 63.6 (#230), o3-mini: 75.1 (#72)
| Benchmark | Mistral Small 3.1 | o3-mini |
|---|---|---|
| LMArena Instruction Following | 1264 | 1337 |
| LiveBench Instruction Following | — | 84.4% |
| IFEval | 75% | — |
Long Context Mistral Small 3.1 leads
Mistral Small 3.1: 39.5 (#178), o3-mini: 33.8 (#256)
| Benchmark | Mistral Small 3.1 | o3-mini |
|---|---|---|
| LMArena Longer Query | 1299 | 1343 |
| Fiction.LiveBench | — | 50% |
Writing & Preference o3-mini leads
Mistral Small 3.1: 37.0 (#259), o3-mini: 50.3 (#182)
| Benchmark | Mistral Small 3.1 | o3-mini |
|---|---|---|
| LMArena Text | 1277 | 1337 |
| LMArena Creative Writing | 1253 | 1286 |
| LMArena Multi-Turn | 1270 | 1320 |
| Short-Story Creative Writing | — | 61.7% |
| EQ-Bench Creative Writing | 761 | — |
| WildBench | 78.8% | — |
| LiveBench Language | — | 50.7% |
Frequently asked questions
Is Mistral Small 3.1 better than o3-mini?
o3-mini is the stronger model overall, scoring 36.7 to 31.7 on the Noometry Index. Mistral Small 3.1 costs 4.8× less per token, which makes it the better buy when o3-mini's lead doesn't matter for your workload.
Which is cheaper, Mistral Small 3.1 or o3-mini?
Mistral Small 3.1 is cheaper. It lists at $0.35 per million input tokens and $0.56 per million output tokens; o3-mini lists at $1.10 and $4.40.
Is Mistral Small 3.1 or o3-mini better for coding?
o3-mini scores higher on coding benchmarks: 40.8 versus 38.3 in the Noometry coding category.
Which has the bigger context window?
o3-mini does, with 200K tokens against 128K.
How many benchmarks do Mistral Small 3.1 and o3-mini share?
21 benchmarks have published results for both models. Mistral Small 3.1 has 28 scored results on Noometry and o3-mini has 51.