# GPT-5 Nano vs Mistral Medium 3.1

> GPT-5 Nano is the stronger model overall, scoring 33.5 to 31.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gpt-5-nano-vs-mistral-medium-3-1
- Last updated: 2026-10-12
- Shared benchmarks: 1

## Summary

- They share 1 benchmark with published results for both. GPT-5 Nano scores higher in 1 category and Mistral Medium 3.1 in 1 category; 2 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Mistral Medium 3.1 leads 55.5 to 39.1.
- GPT-5 Nano is cheaper at $0.05 / $0.40 per million input/output tokens, against $0.40 / $2 for Mistral Medium 3.1.
- GPT-5 Nano accepts more context: 400K tokens versus 131K.

## Snapshot

| | GPT-5 Nano | Mistral Medium 3.1 |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 33.5 | 31.9 |
| Rank | 241 | 266 |
| Context | 400K | 131K |
| Input $/M | $0.05 | $0.40 |
| Output $/M | $0.40 | $2 |
| Weights | Proprietary | Proprietary |

## Coding

- GPT-5 Nano: 33.6 (#254)
- Mistral Medium 3.1: —

| Benchmark | GPT-5 Nano | Mistral Medium 3.1 |
|---|---|---|
| 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 Medium 3.1: —

| Benchmark | GPT-5 Nano | Mistral Medium 3.1 |
|---|---|---|
| Terminal-Bench | 21.8% | — |
| Berkeley Function Calling Leaderboard | 51.5% | — |

## Reasoning

- GPT-5 Nano: 16.3 (#306)
- Mistral Medium 3.1: 10.6 (#341)

| Benchmark | GPT-5 Nano | Mistral Medium 3.1 |
|---|---|---|
| ARC-AGI-2 | 2.6% | — |
| Kagi LLM Benchmark | 62.2% | — |
| NYT Connections (extended) | — | 6.5% |
| ARC-AGI-1 | 20.7% | — |
| Chess Puzzles | 27% | — |
| Thematic Generalization | — | 20.3% |
| LMArena Hard Prompts | 1328 | — |
| Mystery Game Puzzles | 9% | — |
| DTBench | 62.7% | — |
| LMCA | 7.9% | — |
| Epoch Capabilities Index | 139.38 | — |
| ForecastBench | 59.1 | — |

## Math

- GPT-5 Nano: 29.4 (#241)
- Mistral Medium 3.1: —

| Benchmark | GPT-5 Nano | Mistral Medium 3.1 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 20% | — |
| FrontierMath Tier 4 | 2.4% | — |
| OTIS Mock AIME 2024-2025 | 81.1% | — |
| 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 Medium 3.1: —

| Benchmark | GPT-5 Nano | Mistral Medium 3.1 |
|---|---|---|
| GPQA Diamond | 69.4% | — |
| 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 Medium 3.1: —

| Benchmark | GPT-5 Nano | Mistral Medium 3.1 |
|---|---|---|
| LMArena Vision | 1159 | — |
| VPCT | 37.2% | — |

## Multilingual

- GPT-5 Nano: 45.3 (#172)
- Mistral Medium 3.1: —

| Benchmark | GPT-5 Nano | Mistral Medium 3.1 |
|---|---|---|
| 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 Medium 3.1: —

| Benchmark | GPT-5 Nano | Mistral Medium 3.1 |
|---|---|---|
| IFEval | 93.2% | — |
| LMArena Instruction Following | 1306 | — |

## Long Context

- GPT-5 Nano: 31.3 (#281)
- Mistral Medium 3.1: —

| Benchmark | GPT-5 Nano | Mistral Medium 3.1 |
|---|---|---|
| Fiction.LiveBench | 44.4% | — |
| LMArena Longer Query | 1312 | — |

## Writing & Preference

- GPT-5 Nano: 39.1 (#249)
- Mistral Medium 3.1: 55.5 (#145)

| Benchmark | GPT-5 Nano | Mistral Medium 3.1 |
|---|---|---|
| EQ-Bench Creative Writing | 705 | 1476 |
| LMArena Text | 1320 | — |
| LMArena Creative Writing | 1249 | — |
| WildBench | 80.6% | — |
| LMArena Multi-Turn | 1311 | — |

## FAQ

### Is GPT-5 Nano better than Mistral Medium 3.1?

GPT-5 Nano is the stronger model overall, scoring 33.5 to 31.9 on the Noometry Index.

### Which is cheaper, GPT-5 Nano or Mistral Medium 3.1?

GPT-5 Nano is cheaper. It lists at $0.05 per million input tokens and $0.40 per million output tokens; Mistral Medium 3.1 lists at $0.40 and $2.

### Which has the bigger context window?

GPT-5 Nano does, with 400K tokens against 131K.

### How many benchmarks do GPT-5 Nano and Mistral Medium 3.1 share?

1 benchmark has published results for both models. GPT-5 Nano has 49 scored results on Noometry and Mistral Medium 3.1 has 3.