# GPT-5-Codex vs Mistral Small 3.1

> GPT-5-Codex is the stronger model overall, scoring 37.3 to 31.4 on the Noometry Index. Mistral Small 3.1 costs 8.6× less per token, which makes it the better buy when GPT-5-Codex's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-5-codex-vs-mistral-small-3-1
- Last updated: 2026-10-10
- Shared benchmarks: 0

## Summary

- The widest gap is in reasoning, where GPT-5-Codex leads 30.0 to 18.9.
- Mistral Small 3.1 is cheaper at $0.35 / $0.56 per million input/output tokens, against $1.25 / $10 for GPT-5-Codex.
- GPT-5-Codex accepts more context: 400K tokens versus 128K.
- Mistral Small 3.1 has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-5-Codex | Mistral Small 3.1 |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 37.3 | 31.4 |
| Rank | 190 | 263 |
| Context | 400K | 128K |
| Input $/M | $1.25 | $0.35 |
| Output $/M | $10 | $0.56 |
| Weights | Proprietary | Open |

## Coding

- GPT-5-Codex: 41.9 (#100)
- Mistral Small 3.1: 37.7 (#175)

| Benchmark | GPT-5-Codex | Mistral Small 3.1 |
|---|---|---|
| WeirdML | 54.5% | — |
| LMArena Coding | — | 1309 |

## Agentic & Tool Use

- GPT-5-Codex: 30.8 (#66)
- Mistral Small 3.1: —

| Benchmark | GPT-5-Codex | Mistral Small 3.1 |
|---|---|---|
| Terminal-Bench | 44.3% | — |

## Reasoning

- GPT-5-Codex: 30.0 (#80)
- Mistral Small 3.1: 18.9 (#249)

| Benchmark | GPT-5-Codex | Mistral Small 3.1 |
|---|---|---|
| Kagi LLM Benchmark | 70.3% | — |
| Chess Puzzles | — | 1% |
| LMArena Hard Prompts | — | 1278 |
| Epoch Capabilities Index | — | 127.48 |

## Math

- GPT-5-Codex: —
- Mistral Small 3.1: 13.7 (#295)

| Benchmark | GPT-5-Codex | Mistral Small 3.1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 3.9% |
| Omni-MATH | — | 24.8% |
| LMArena Math | — | 1261 |

## Knowledge

- GPT-5-Codex: —
- Mistral Small 3.1: 22.6 (#266)

| Benchmark | GPT-5-Codex | Mistral Small 3.1 |
|---|---|---|
| GPQA Diamond | — | 41.9% |
| MMLU-Pro | — | 61% |
| GPQA (HELM) | — | 39.2% |
| LMArena Expert | — | 1258 |

## Multimodal

- GPT-5-Codex: —
- Mistral Small 3.1: 32.6 (#93)

| Benchmark | GPT-5-Codex | Mistral Small 3.1 |
|---|---|---|
| LMArena Vision | — | 1136 |

## Multilingual

- GPT-5-Codex: —
- Mistral Small 3.1: 41.4 (#204)

| Benchmark | GPT-5-Codex | Mistral Small 3.1 |
|---|---|---|
| LMArena Non-English | — | 1255 |
| LMArena Chinese | — | 1254 |
| LMArena French | — | 1270 |
| LMArena German | — | 1266 |
| LMArena Japanese | — | 1210 |
| LMArena Korean | — | 1206 |
| LMArena Russian | — | 1263 |
| LMArena Spanish | — | 1283 |

## Instruction Following

- GPT-5-Codex: —
- Mistral Small 3.1: 63.8 (#225)

| Benchmark | GPT-5-Codex | Mistral Small 3.1 |
|---|---|---|
| IFEval | — | 75% |
| LMArena Instruction Following | — | 1264 |

## Long Context

- GPT-5-Codex: —
- Mistral Small 3.1: 39.5 (#172)

| Benchmark | GPT-5-Codex | Mistral Small 3.1 |
|---|---|---|
| LMArena Longer Query | — | 1300 |

## Writing & Preference

- GPT-5-Codex: —
- Mistral Small 3.1: 37.2 (#254)

| Benchmark | GPT-5-Codex | Mistral Small 3.1 |
|---|---|---|
| LMArena Text | — | 1278 |
| LMArena Creative Writing | — | 1253 |
| EQ-Bench Creative Writing | — | 761 |
| WildBench | — | 78.8% |
| LMArena Multi-Turn | — | 1270 |

## FAQ

### Is GPT-5-Codex better than Mistral Small 3.1?

GPT-5-Codex is the stronger model overall, scoring 37.3 to 31.4 on the Noometry Index. Mistral Small 3.1 costs 8.6× less per token, which makes it the better buy when GPT-5-Codex's lead doesn't matter for your workload.

### Which is cheaper, GPT-5-Codex or Mistral Small 3.1?

Mistral Small 3.1 is cheaper. It lists at $0.35 per million input tokens and $0.56 per million output tokens; GPT-5-Codex lists at $1.25 and $10.

### Is GPT-5-Codex or Mistral Small 3.1 better for coding?

GPT-5-Codex scores higher on coding benchmarks: 41.9 versus 37.7 in the Noometry coding category.

### Which has the bigger context window?

GPT-5-Codex does, with 400K tokens against 128K.

### How many benchmarks do GPT-5-Codex and Mistral Small 3.1 share?

0 benchmarks have published results for both models. GPT-5-Codex has 3 scored results on Noometry and Mistral Small 3.1 has 28.