# GPT-5.2 Codex vs Mistral Small 3

> GPT-5.2 Codex is the stronger model overall, scoring 42.6 to 31.2 on the Noometry Index. Mistral Small 3 costs 84× less per token, which makes it the better buy when GPT-5.2 Codex's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-5-2-codex-vs-mistral-small-3
- Last updated: 2026-10-11
- Shared benchmarks: 0

## Summary

- The widest gap is in coding, where GPT-5.2 Codex leads 45.5 to 36.5.
- Mistral Small 3 is cheaper at $0.05 / $0.08 per million input/output tokens, against $1.75 / $14 for GPT-5.2 Codex.
- GPT-5.2 Codex accepts more context: 400K tokens versus 33K.
- Mistral Small 3 has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-5.2 Codex | Mistral Small 3 |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 42.6 | 31.2 |
| Rank | 111 | 278 |
| Context | 400K | 33K |
| Input $/M | $1.75 | $0.05 |
| Output $/M | $14 | $0.08 |
| Weights | Proprietary | Open |

## Coding

- GPT-5.2 Codex: 45.5 (#71)
- Mistral Small 3: 36.5 (#207)

| Benchmark | GPT-5.2 Codex | Mistral Small 3 |
|---|---|---|
| SWE-bench Verified (bash only) | 72.8% | — |
| LMArena WebDev | 1339 | — |
| SWE-bench Multilingual | 66.3% | — |
| BigCodeBench Instruct | — | 45.3% |
| LMArena Coding | — | 1246 |
| BigCodeBench Complete | — | 50.4% |
| ALE-Bench | 1,300 | — |

## Agentic & Tool Use

- GPT-5.2 Codex: 41.0 (#22)
- Mistral Small 3: —

| Benchmark | GPT-5.2 Codex | Mistral Small 3 |
|---|---|---|
| Terminal-Bench | 66.5% | — |

## Reasoning

- GPT-5.2 Codex: —
- Mistral Small 3: 18.9 (#273)

| Benchmark | GPT-5.2 Codex | Mistral Small 3 |
|---|---|---|
| Chess Puzzles | — | 0% |
| LMArena Hard Prompts | — | 1233 |
| Epoch Capabilities Index | — | 127.07 |

## Math

- GPT-5.2 Codex: —
- Mistral Small 3: 16.3 (#295)

| Benchmark | GPT-5.2 Codex | Mistral Small 3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 6.7% |
| LMArena Math | — | 1240 |

## Knowledge

- GPT-5.2 Codex: —
- Mistral Small 3: 25.1 (#263)

| Benchmark | GPT-5.2 Codex | Mistral Small 3 |
|---|---|---|
| GPQA Diamond | — | 47.3% |
| Confabulations | — | 25.2% |
| LMArena Expert | — | 1202 |

## Multilingual

- GPT-5.2 Codex: —
- Mistral Small 3: 37.3 (#236)

| Benchmark | GPT-5.2 Codex | Mistral Small 3 |
|---|---|---|
| LMArena Non-English | — | 1198 |
| LMArena Chinese | — | 1204 |
| LMArena French | — | 1203 |
| LMArena German | — | 1211 |
| LMArena Japanese | — | 1111 |
| LMArena Korean | — | 1188 |
| LMArena Russian | — | 1216 |

## Instruction Following

- GPT-5.2 Codex: —
- Mistral Small 3: 63.7 (#229)

| Benchmark | GPT-5.2 Codex | Mistral Small 3 |
|---|---|---|
| LMArena Instruction Following | — | 1214 |

## Long Context

- GPT-5.2 Codex: —
- Mistral Small 3: 37.8 (#211)

| Benchmark | GPT-5.2 Codex | Mistral Small 3 |
|---|---|---|
| LMArena Longer Query | — | 1246 |

## Writing & Preference

- GPT-5.2 Codex: —
- Mistral Small 3: 32.2 (#280)

| Benchmark | GPT-5.2 Codex | Mistral Small 3 |
|---|---|---|
| LMArena Text | — | 1234 |
| LMArena Creative Writing | — | 1195 |
| EQ-Bench Creative Writing | — | 707 |
| LMArena Multi-Turn | — | 1217 |

## FAQ

### Is GPT-5.2 Codex better than Mistral Small 3?

GPT-5.2 Codex is the stronger model overall, scoring 42.6 to 31.2 on the Noometry Index. Mistral Small 3 costs 84× less per token, which makes it the better buy when GPT-5.2 Codex's lead doesn't matter for your workload.

### Which is cheaper, GPT-5.2 Codex or Mistral Small 3?

Mistral Small 3 is cheaper. It lists at $0.05 per million input tokens and $0.08 per million output tokens; GPT-5.2 Codex lists at $1.75 and $14.

### Is GPT-5.2 Codex or Mistral Small 3 better for coding?

GPT-5.2 Codex scores higher on coding benchmarks: 45.5 versus 36.5 in the Noometry coding category.

### Which has the bigger context window?

GPT-5.2 Codex does, with 400K tokens against 33K.

### How many benchmarks do GPT-5.2 Codex and Mistral Small 3 share?

0 benchmarks have published results for both models. GPT-5.2 Codex has 5 scored results on Noometry and Mistral Small 3 has 24.