# GPT-4 Turbo vs Mistral Medium

> Mistral Medium is the stronger model overall, scoring 36.0 to 30.3 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gpt-4-turbo-vs-mistral-medium
- Last updated: 2026-10-10
- Shared benchmarks: 24

## Summary

- They share 24 benchmarks with published results for both. GPT-4 Turbo scores higher in 0 categories and Mistral Medium in 9 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where Mistral Medium leads 27.2 to 8.6.
- The biggest single-benchmark swing is MATH Level 5: 46.7% for GPT-4 Turbo and 81.6% for Mistral Medium.
- Mistral Medium is cheaper at $1.50 / $7.50 per million input/output tokens, against $10 / $30 for GPT-4 Turbo.
- Mistral Medium accepts more context: 262K tokens versus 128K.
- Mistral Medium has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-4 Turbo | Mistral Medium |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 30.3 | 36.0 |
| Rank | 281 | 211 |
| Context | 128K | 262K |
| Input $/M | $10 | $1.50 |
| Output $/M | $30 | $7.50 |
| Weights | Proprietary | Open |

## Coding

- GPT-4 Turbo: 33.4 (#247)
- Mistral Medium: 33.8 (#241)

| Benchmark | GPT-4 Turbo | Mistral Medium |
|---|---|---|
| WeirdML | 18% | 43.7% |
| LMArena Coding | 1268 | 1434 |
| FrontierCode | — | 8% |
| SciCode | — | 40.2% |
| BigCodeBench Instruct | 48.2% | — |
| BigCodeBench Complete | 58.2% | — |
| ALE-Bench | — | 763.98 |
| HumanEval+ | 86.6% | — |
| MBPP+ | 73.3% | — |

## Agentic & Tool Use

- GPT-4 Turbo: —
- Mistral Medium: 28.1 (#84)

| Benchmark | GPT-4 Turbo | Mistral Medium |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 37.7% |
| METR Time Horizons | 36.7% | — |

## Reasoning

- GPT-4 Turbo: 14.9 (#311)
- Mistral Medium: 23.3 (#165)

| Benchmark | GPT-4 Turbo | Mistral Medium |
|---|---|---|
| LMArena Hard Prompts | 1251 | 1426 |
| DTBench | 61.6% | 75.5% |
| LMCA | 9.8% | 26.1% |
| SimpleBench | 25.1% | — |
| Kagi LLM Benchmark | — | 50% |
| CritPt | — | 0% |
| Chess Puzzles | 6% | — |
| Surface Evolver Bench | — | 26.9% |
| Epoch Capabilities Index | 127.25 | — |
| ForecastBench | 59.4 | — |

## Math

- GPT-4 Turbo: 8.6 (#316)
- Mistral Medium: 27.2 (#238)

| Benchmark | GPT-4 Turbo | Mistral Medium |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 6.7% | 32.2% |
| LMArena Math | 1272 | 1409 |
| MATH Level 5 | 46.7% | 81.6% |
| FrontierMath (Tiers 1-3) | 0.7% | — |
| ProofBench | — | 9% |
| FrontierMath (Feb 2025 set) | — | 0.3% |

## Knowledge

- GPT-4 Turbo: 24.3 (#263)
- Mistral Medium: 24.9 (#260)

| Benchmark | GPT-4 Turbo | Mistral Medium |
|---|---|---|
| GPQA Diamond | 46.6% | 59.5% |
| LMArena Expert | 1223 | 1408 |
| Humanity's Last Exam | — | 4.5% |
| Confabulations | 28.4% | — |
| Vectara Hallucination Rate | — | 22.7% |
| MMLU | 81.3% | — |

## Multimodal

- GPT-4 Turbo: 30.0 (#104)
- Mistral Medium: 34.6 (#82)

| Benchmark | GPT-4 Turbo | Mistral Medium |
|---|---|---|
| LMArena Vision | 1090 | 1172 |

## Multilingual

- GPT-4 Turbo: 40.7 (#211)
- Mistral Medium: 52.3 (#86)

| Benchmark | GPT-4 Turbo | Mistral Medium |
|---|---|---|
| LMArena Non-English | 1245 | 1408 |
| LMArena Chinese | 1242 | 1448 |
| LMArena French | 1275 | 1460 |
| LMArena German | 1259 | 1433 |
| LMArena Japanese | 1194 | 1378 |
| LMArena Korean | 1187 | 1382 |
| LMArena Russian | 1259 | 1411 |
| LMArena Spanish | 1260 | 1433 |

## Instruction Following

- GPT-4 Turbo: 66.0 (#211)
- Mistral Medium: 73.9 (#111)

| Benchmark | GPT-4 Turbo | Mistral Medium |
|---|---|---|
| LMArena Instruction Following | 1250 | 1398 |

## Long Context

- GPT-4 Turbo: 38.0 (#200)
- Mistral Medium: 42.9 (#108)

| Benchmark | GPT-4 Turbo | Mistral Medium |
|---|---|---|
| LMArena Longer Query | 1254 | 1406 |

## Writing & Preference

- GPT-4 Turbo: 47.9 (#201)
- Mistral Medium: 60.2 (#97)

| Benchmark | GPT-4 Turbo | Mistral Medium |
|---|---|---|
| LMArena Text | 1272 | 1424 |
| LMArena Creative Writing | 1269 | 1391 |
| LMArena Multi-Turn | 1267 | 1418 |
| Short-Story Creative Writing | — | 77.3% |

## FAQ

### Is GPT-4 Turbo better than Mistral Medium?

Mistral Medium is the stronger model overall, scoring 36.0 to 30.3 on the Noometry Index.

### Which is cheaper, GPT-4 Turbo or Mistral Medium?

Mistral Medium is cheaper. It lists at $1.50 per million input tokens and $7.50 per million output tokens; GPT-4 Turbo lists at $10 and $30.

### Is GPT-4 Turbo or Mistral Medium better for coding?

They score almost the same on coding (33.4 vs 33.8); test both on your own repository before choosing.

### Which has the bigger context window?

Mistral Medium does, with 262K tokens against 128K.

### How many benchmarks do GPT-4 Turbo and Mistral Medium share?

24 benchmarks have published results for both models. GPT-4 Turbo has 36 scored results on Noometry and Mistral Medium has 36.