# GPT-5 Nano vs Mistral Small 3.2

> GPT-5 Nano is the stronger model overall, scoring 33.5 to 31.2 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gpt-5-nano-vs-mistral-small-3-2
- Last updated: 2026-10-12
- Shared benchmarks: 6

## Summary

- They share 6 benchmarks with published results for both. GPT-5 Nano scores higher in 2 categories and Mistral Small 3.2 in 2 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GPT-5 Nano leads 35.9 to 26.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 81.1% for GPT-5 Nano and 30.3% for Mistral Small 3.2.
- Both cost about the same: $0.05 input and $0.40 output per million tokens.
- GPT-5 Nano accepts more context: 400K tokens versus 256K.
- Mistral Small 3.2 has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-5 Nano | Mistral Small 3.2 |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 33.5 | 31.2 |
| Rank | 241 | 280 |
| Context | 400K | 256K |
| Input $/M | $0.05 | $0.0938 |
| Output $/M | $0.40 | $0.25 |
| Weights | Proprietary | Open |

## Coding

- GPT-5 Nano: 33.6 (#254)
- Mistral Small 3.2: —

| Benchmark | GPT-5 Nano | Mistral Small 3.2 |
|---|---|---|
| SWE-bench Verified (bash only) | 34.8% | — |
| WeirdML | 38.1% | — |
| LMArena Coding | 1351 | — |
| ALE-Bench | 718.67 | — |

## Agentic & Tool Use

- GPT-5 Nano: 25.8 (#106)
- Mistral Small 3.2: —

| Benchmark | GPT-5 Nano | Mistral Small 3.2 |
|---|---|---|
| Terminal-Bench | 21.8% | — |
| Berkeley Function Calling Leaderboard | 51.5% | — |

## Reasoning

- GPT-5 Nano: 16.3 (#306)
- Mistral Small 3.2: 18.1 (#287)

| Benchmark | GPT-5 Nano | Mistral Small 3.2 |
|---|---|---|
| Kagi LLM Benchmark | 62.2% | 40.4% |
| Chess Puzzles | 27% | 1% |
| Epoch Capabilities Index | 139.38 | 131.74 |
| ARC-AGI-2 | 2.6% | — |
| ARC-AGI-1 | 20.7% | — |
| LMArena Hard Prompts | 1328 | — |
| Mystery Game Puzzles | 9% | — |
| DTBench | 62.7% | — |
| LMCA | 7.9% | — |
| ForecastBench | 59.1 | — |

## Math

- GPT-5 Nano: 29.4 (#241)
- Mistral Small 3.2: 26.3 (#260)

| Benchmark | GPT-5 Nano | Mistral Small 3.2 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 81.1% | 30.3% |
| FrontierMath (Tiers 1-3) | 20% | — |
| FrontierMath Tier 4 | 2.4% | — |
| ProofBench | 12% | — |
| Omni-MATH | 54.6% | — |
| LMArena Math | 1317 | — |
| MATH Level 5 | 95.2% | — |
| FrontierMath (Feb 2025 set) | 8.3% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |

## Knowledge

- GPT-5 Nano: 35.9 (#178)
- Mistral Small 3.2: 26.7 (#256)

| Benchmark | GPT-5 Nano | Mistral Small 3.2 |
|---|---|---|
| GPQA Diamond | 69.4% | 49.1% |
| SimpleQA Verified | 11.7% | — |
| MMLU-Pro | 77.8% | — |
| Vectara Hallucination Rate | 10.5% | — |
| GPQA (HELM) | 67.9% | — |
| LMArena Expert | 1321 | — |

## Multimodal

- GPT-5 Nano: 31.3 (#108)
- Mistral Small 3.2: —

| Benchmark | GPT-5 Nano | Mistral Small 3.2 |
|---|---|---|
| LMArena Vision | 1159 | — |
| VPCT | 37.2% | — |

## Multilingual

- GPT-5 Nano: 45.3 (#172)
- Mistral Small 3.2: —

| Benchmark | GPT-5 Nano | Mistral Small 3.2 |
|---|---|---|
| LMArena Non-English | 1313 | — |
| LMArena Chinese | 1356 | — |
| LMArena German | 1327 | — |
| LMArena Japanese | 1226 | — |
| LMArena Korean | 1269 | — |
| LMArena Russian | 1296 | — |
| LMArena Spanish | 1360 | — |

## Instruction Following

- GPT-5 Nano: 75.0 (#79)
- Mistral Small 3.2: —

| Benchmark | GPT-5 Nano | Mistral Small 3.2 |
|---|---|---|
| IFEval | 93.2% | — |
| LMArena Instruction Following | 1306 | — |

## Long Context

- GPT-5 Nano: 31.3 (#281)
- Mistral Small 3.2: —

| Benchmark | GPT-5 Nano | Mistral Small 3.2 |
|---|---|---|
| Fiction.LiveBench | 44.4% | — |
| LMArena Longer Query | 1312 | — |

## Writing & Preference

- GPT-5 Nano: 39.1 (#249)
- Mistral Small 3.2: 45.0 (#224)

| Benchmark | GPT-5 Nano | Mistral Small 3.2 |
|---|---|---|
| EQ-Bench Creative Writing | 705 | 1255 |
| LMArena Text | 1320 | — |
| LMArena Creative Writing | 1249 | — |
| WildBench | 80.6% | — |
| LMArena Multi-Turn | 1311 | — |

## FAQ

### Is GPT-5 Nano better than Mistral Small 3.2?

GPT-5 Nano is the stronger model overall, scoring 33.5 to 31.2 on the Noometry Index.

### Which is cheaper, GPT-5 Nano or Mistral Small 3.2?

Mistral Small 3.2 is cheaper. It lists at $0.0938 per million input tokens and $0.25 per million output tokens; GPT-5 Nano lists at $0.05 and $0.40.

### Which has the bigger context window?

GPT-5 Nano does, with 400K tokens against 256K.

### How many benchmarks do GPT-5 Nano and Mistral Small 3.2 share?

6 benchmarks have published results for both models. GPT-5 Nano has 49 scored results on Noometry and Mistral Small 3.2 has 6.