# 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.

- Canonical page: https://noometry.com/compare/mistral-small-3-2-vs-o1
- Last updated: 2026-10-10
- Shared benchmarks: 4

## Summary

- 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.

## Snapshot

| | Mistral Small 3.2 | o1 |
|---|---|---|
| Provider | Mistral AI | OpenAI |
| Noometry Index | 30.8 | 40.6 |
| Rank | 271 | 140 |
| Context | 256K | 200K |
| Input $/M | $0.0938 | $15 |
| Output $/M | $0.25 | $60 |
| Weights | Open | Proprietary |

## Coding

- 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

- Mistral Small 3.2: —
- o1: 24.3 (#111)

| Benchmark | Mistral Small 3.2 | o1 |
|---|---|---|
| Cybench | — | 10% |
| METR Time Horizons | — | 51.1% |

## Reasoning

- 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

- 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

- 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

- 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

- 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

- 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

- Mistral Small 3.2: —
- o1: 50.3 (#9)

| Benchmark | Mistral Small 3.2 | o1 |
|---|---|---|
| Fiction.LiveBench | — | 83.3% |
| LMArena Longer Query | — | 1378 |

## Writing & Preference

- 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% |

## FAQ

### 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.