Model comparison
Mistral Small 3.2 vs o1
o1 is the stronger model overall, scoring 40.6 to 30.8 on the Noometry Index. Mistral Small 3.2 costs 198× less per token, which makes it the better buy when o1's lead doesn't matter for your workload.
Last verified . 4 shared benchmarks.
Mistral AISummary
- They share 4 benchmarks with published results for both. Mistral Small 3.2 scores higher in 0 categories and o1 in 4 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where o1 leads 41.5 to 26.8.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 30.3% for Mistral Small 3.2 and 73.3% for o1.
- Mistral Small 3.2 is cheaper at $0.0938 / $0.25 per million input/output tokens, against $15 / $60 for o1.
- Mistral Small 3.2 accepts more context: 256K tokens versus 200K.
- Mistral Small 3.2 has downloadable open weights; the other is API-only.
Side by side
| Mistral Small 3.2 | o1 | |
|---|---|---|
| Provider | Mistral AI | OpenAI |
| Noometry Index | 30.8 | 40.6 |
| Released | 2025-06-20 | 2024-09-12 |
| Weights | Open | Proprietary |
| Context window | 256K | 200K |
| Max output | 16K | 100K |
| Input $ / M tokens | $0.0938 | $15 |
| Output $ / M tokens | $0.25 | $60 |
| Results tracked | 6 | 52 |
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Category by category
Coding Not comparable
Mistral Small 3.2: —, o1: 45.7 (#64)
| Benchmark | Mistral Small 3.2 | o1 |
|---|---|---|
| Aider Polyglot | — | 61.7% |
| WeirdML | — | 47.6% |
| LiveBench Coding | — | 69.7% |
| LMArena Coding | — | 1367 |
| CadEval | — | 56% |
| HumanEval+ | — | 89% |
| MBPP+ | — | 80.2% |
Agentic & Tool Use Not comparable
Mistral Small 3.2: —, o1: 24.3 (#111)
| Benchmark | Mistral Small 3.2 | o1 |
|---|---|---|
| Cybench | — | 10% |
| METR Time Horizons | — | 51.1% |
Reasoning o1 leads
Mistral Small 3.2: 17.5 (#282), o1: 27.5 (#103)
| Benchmark | Mistral Small 3.2 | o1 |
|---|---|---|
| Chess Puzzles | 1% | 15% |
| Epoch Capabilities Index | 131.73 | 141.92 |
| SimpleBench | — | 41.7% |
| Kagi LLM Benchmark | 40.4% | — |
| ARC-AGI-1 | — | 30.7% |
| EnigmaEval | — | 5.7% |
| LiveBench Reasoning | — | 91.6% |
| LMArena Hard Prompts | — | 1372 |
| DTBench | — | 74.7% |
| LiveBench Data Analysis | — | 65.5% |
| LMCA | — | 22.3% |
| LiveBench | — | 75.7% |
Math o1 leads
Mistral Small 3.2: 24.9 (#251), o1: 34.9 (#150)
| Benchmark | Mistral Small 3.2 | o1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 30.3% | 73.3% |
| FrontierMath (Tiers 1-3) | — | 14.7% |
| LiveBench Math | — | 80.3% |
| LMArena Math | — | 1388 |
| MATH Level 5 | — | 94.7% |
| FrontierMath (Feb 2025 set) | — | 9.3% |
Knowledge o1 leads
Mistral Small 3.2: 26.8 (#249), o1: 41.5 (#101)
| Benchmark | Mistral Small 3.2 | o1 |
|---|---|---|
| GPQA Diamond | 49.1% | 76.8% |
| Humanity's Last Exam | — | 8% |
| SimpleQA Verified | — | 41.1% |
| Confabulations | — | 11.7% |
| LMArena Expert | — | 1362 |
Multimodal Not comparable
Mistral Small 3.2: —, o1: 33.6 (#87)
| Benchmark | Mistral Small 3.2 | o1 |
|---|---|---|
| LMArena Vision | — | 1168 |
| GeoBench | — | 80% |
| VPCT | — | 37% |
| SpatialViz-Bench | — | 41.4% |
Multilingual Not comparable
Mistral Small 3.2: —, o1: 48.8 (#137)
| Benchmark | Mistral Small 3.2 | o1 |
|---|---|---|
| LMArena Non-English | — | 1359 |
| LMArena Chinese | — | 1394 |
| LMArena French | — | 1343 |
| LMArena German | — | 1337 |
| LMArena Japanese | — | 1346 |
| LMArena Korean | — | 1396 |
| LMArena Russian | — | 1356 |
| LMArena Spanish | — | 1345 |
Instruction Following Not comparable
Mistral Small 3.2: —, o1: 75.0 (#82)
| Benchmark | Mistral Small 3.2 | o1 |
|---|---|---|
| LiveBench Instruction Following | — | 81.5% |
| LMArena Instruction Following | — | 1368 |
Long Context Not comparable
Mistral Small 3.2: —, o1: 50.3 (#9)
| Benchmark | Mistral Small 3.2 | o1 |
|---|---|---|
| Fiction.LiveBench | — | 83.3% |
| LMArena Longer Query | — | 1378 |
Writing & Preference o1 leads
Mistral Small 3.2: 45.1 (#219), o1: 55.8 (#139)
| Benchmark | Mistral Small 3.2 | o1 |
|---|---|---|
| LMArena Text | — | 1366 |
| LMArena Creative Writing | — | 1347 |
| Short-Story Creative Writing | — | 70.2% |
| EQ-Bench Creative Writing | 1255 | — |
| LMArena Multi-Turn | — | 1368 |
| LiveBench Language | — | 65.4% |
Frequently asked questions
Is Mistral Small 3.2 better than o1?
o1 is the stronger model overall, scoring 40.6 to 30.8 on the Noometry Index. Mistral Small 3.2 costs 198× less per token, which makes it the better buy when o1's lead doesn't matter for your workload.
Which is cheaper, Mistral Small 3.2 or o1?
Mistral Small 3.2 is cheaper. It lists at $0.0938 per million input tokens and $0.25 per million output tokens; o1 lists at $15 and $60.
Which has the bigger context window?
Mistral Small 3.2 does, with 256K tokens against 200K.
How many benchmarks do Mistral Small 3.2 and o1 share?
4 benchmarks have published results for both models. Mistral Small 3.2 has 6 scored results on Noometry and o1 has 52.