# GPT-4o mini vs Mistral Large 3

> Mistral Large 3 is the stronger model overall, scoring 39.1 to 25.5 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gpt-4o-mini-vs-mistral-large-3
- Last updated: 2026-10-11
- Shared benchmarks: 20

## Summary

- They share 20 benchmarks with published results for both. GPT-4o mini scores higher in 0 categories and Mistral Large 3 in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Mistral Large 3 leads 38.7 to 10.4.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 28.8% for GPT-4o mini and 50.9% for Mistral Large 3.
- GPT-4o mini is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.25 / $0.75 for Mistral Large 3.
- Mistral Large 3 accepts more context: 262K tokens versus 128K.
- Mistral Large 3 has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-4o mini | Mistral Large 3 |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 25.5 | 39.1 |
| Rank | 343 | 176 |
| Context | 128K | 262K |
| Input $/M | $0.15 | $0.25 |
| Output $/M | $0.60 | $0.75 |
| Weights | Proprietary | Open |

## Coding

- GPT-4o mini: 22.0 (#335)
- Mistral Large 3: 34.4 (#237)

| Benchmark | GPT-4o mini | Mistral Large 3 |
|---|---|---|
| LMArena Coding | 1290 | 1448 |
| Aider Polyglot | 3.6% | — |
| LMArena WebDev | — | 1230 |
| WeirdML | 11.8% | — |
| BigCodeBench Instruct | 46.1% | — |
| LiveBench Coding | 43.1% | — |
| BigCodeBench Complete | 57.4% | — |
| HumanEval+ | 83.5% | — |
| MBPP+ | 72.2% | — |

## Agentic & Tool Use

- GPT-4o mini: 27.5 (#101)
- Mistral Large 3: —

| Benchmark | GPT-4o mini | Mistral Large 3 |
|---|---|---|
| BALROG | 17.4% | — |

## Reasoning

- GPT-4o mini: 8.7 (#347)
- Mistral Large 3: 15.2 (#319)

| Benchmark | GPT-4o mini | Mistral Large 3 |
|---|---|---|
| Kagi LLM Benchmark | 28.8% | 50.9% |
| LMArena Hard Prompts | 1267 | 1429 |
| ARC-AGI-2 | 0% | — |
| SimpleBench | 10.7% | — |
| NYT Connections (extended) | — | 7.5% |
| Chess Puzzles | 0% | — |
| Thematic Generalization | — | 23% |
| LiveBench Reasoning | 32.8% | — |
| Mystery Game Puzzles | 12% | — |
| DTBench | 54.4% | — |
| LiveBench Data Analysis | 50% | — |
| LMCA | 10.4% | — |
| Epoch Capabilities Index | 126.56 | — |
| LiveBench | 41.3% | — |
| PIQA | 88.7% | — |

## Math

- GPT-4o mini: 10.4 (#314)
- Mistral Large 3: 38.7 (#129)

| Benchmark | GPT-4o mini | Mistral Large 3 |
|---|---|---|
| LMArena Math | 1267 | 1414 |
| FrontierMath (Tiers 1-3) | 0.7% | — |
| OTIS Mock AIME 2024-2025 | 6.9% | — |
| Omni-MATH | 28% | — |
| LiveBench Math | 36.3% | — |
| MATH Level 5 | 52.6% | — |
| GSM8K | 91.3% | — |

## Knowledge

- GPT-4o mini: 17.7 (#284)
- Mistral Large 3: 36.0 (#177)

| Benchmark | GPT-4o mini | Mistral Large 3 |
|---|---|---|
| LMArena Expert | 1235 | 1421 |
| GPQA Diamond | 37.7% | — |
| SimpleQA Verified | 8.3% | — |
| MMLU-Pro | 60.3% | — |
| Confabulations | 37.2% | — |
| Vectara Hallucination Rate | — | 14.5% |
| GPQA (HELM) | 36.8% | — |
| BoolQ | 88.7% | — |
| MMLU | 81.8% | — |

## Multimodal

- GPT-4o mini: 25.9 (#122)
- Mistral Large 3: 38.2 (#66)

| Benchmark | GPT-4o mini | Mistral Large 3 |
|---|---|---|
| LMArena Vision | 1066 | 1221 |
| Video-MME | 64.8% | — |
| GeoBench | 64% | — |
| VPCT | 34% | — |

## Multilingual

- GPT-4o mini: 42.0 (#199)
- Mistral Large 3: 52.5 (#84)

| Benchmark | GPT-4o mini | Mistral Large 3 |
|---|---|---|
| LMArena Non-English | 1266 | 1413 |
| LMArena Chinese | 1265 | 1447 |
| LMArena French | 1297 | 1455 |
| LMArena German | 1272 | 1437 |
| LMArena Japanese | 1216 | 1394 |
| LMArena Korean | 1195 | 1384 |
| LMArena Russian | 1275 | 1411 |
| LMArena Spanish | 1276 | 1440 |

## Instruction Following

- GPT-4o mini: 61.9 (#239)
- Mistral Large 3: 74.0 (#108)

| Benchmark | GPT-4o mini | Mistral Large 3 |
|---|---|---|
| LMArena Instruction Following | 1258 | 1403 |
| LiveBench Instruction Following | 56.8% | — |
| IFEval | 78.2% | — |

## Long Context

- GPT-4o mini: 39.1 (#186)
- Mistral Large 3: 43.1 (#105)

| Benchmark | GPT-4o mini | Mistral Large 3 |
|---|---|---|
| LMArena Longer Query | 1289 | 1413 |

## Writing & Preference

- GPT-4o mini: 39.5 (#248)
- Mistral Large 3: 60.0 (#101)

| Benchmark | GPT-4o mini | Mistral Large 3 |
|---|---|---|
| LMArena Text | 1286 | 1428 |
| LMArena Creative Writing | 1268 | 1386 |
| EQ-Bench Creative Writing | 873 | 1412 |
| LMArena Multi-Turn | 1285 | 1429 |
| Short-Story Creative Writing | 67.2% | — |
| WildBench | 79.1% | — |
| LiveBench Language | 28.6% | — |

## FAQ

### Is GPT-4o mini better than Mistral Large 3?

Mistral Large 3 is the stronger model overall, scoring 39.1 to 25.5 on the Noometry Index.

### Which is cheaper, GPT-4o mini or Mistral Large 3?

GPT-4o mini is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Mistral Large 3 lists at $0.25 and $0.75.

### Is GPT-4o mini or Mistral Large 3 better for coding?

Mistral Large 3 scores higher on coding benchmarks: 34.4 versus 22.0 in the Noometry coding category.

### Which has the bigger context window?

Mistral Large 3 does, with 262K tokens against 128K.

### How many benchmarks do GPT-4o mini and Mistral Large 3 share?

20 benchmarks have published results for both models. GPT-4o mini has 60 scored results on Noometry and Mistral Large 3 has 24.