# GPT-4.1 mini vs Mistral Large 3

> Mistral Large 3 is the stronger model overall, scoring 38.6 to 33.5 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gpt-4-1-mini-vs-mistral-large-3
- Last updated: 2026-10-10
- Shared benchmarks: 20

## Summary

- They share 20 benchmarks with published results for both. GPT-4.1 mini scores higher in 0 categories and Mistral Large 3 in 9 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where Mistral Large 3 leads 36.0 to 23.1.
- Mistral Large 3 is cheaper at $0.25 / $0.75 per million input/output tokens, against $0.40 / $1.60 for GPT-4.1 mini.
- GPT-4.1 mini accepts more context: 1.05M tokens versus 262K.
- Mistral Large 3 has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-4.1 mini | Mistral Large 3 |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 33.5 | 38.6 |
| Rank | 232 | 172 |
| Context | 1.05M | 262K |
| Input $/M | $0.40 | $0.25 |
| Output $/M | $1.60 | $0.75 |
| Weights | Proprietary | Open |

## Coding

- GPT-4.1 mini: 30.4 (#286)
- Mistral Large 3: 34.1 (#230)

| Benchmark | GPT-4.1 mini | Mistral Large 3 |
|---|---|---|
| LMArena Coding | 1367 | 1447 |
| SWE-bench Verified (bash only) | 23.9% | — |
| Aider Polyglot | 32.4% | — |
| LMArena WebDev | — | 1230 |
| SciCode | 40.4% | — |
| WeirdML | 37.6% | — |
| BigCodeBench Instruct | 48.9% | — |
| CadEval | 16% | — |

## Agentic & Tool Use

- GPT-4.1 mini: 33.0 (#52)
- Mistral Large 3: —

| Benchmark | GPT-4.1 mini | Mistral Large 3 |
|---|---|---|
| Berkeley Function Calling Leaderboard | 50.5% | — |

## Reasoning

- GPT-4.1 mini: 10.9 (#335)
- Mistral Large 3: 14.6 (#314)

| Benchmark | GPT-4.1 mini | Mistral Large 3 |
|---|---|---|
| Kagi LLM Benchmark | 48.6% | 50.9% |
| LMArena Hard Prompts | 1349 | 1429 |
| ARC-AGI-2 | 0% | — |
| NYT Connections (extended) | — | 7.5% |
| ARC-AGI-1 | 3.5% | — |
| CritPt | 0% | — |
| Chess Puzzles | 7% | — |
| Thematic Generalization | — | 23% |
| Mystery Game Puzzles | 7% | — |
| DTBench | 68.8% | — |
| LMCA | 21.1% | — |
| Epoch Capabilities Index | 135.01 | — |

## Math

- GPT-4.1 mini: 23.1 (#264)
- Mistral Large 3: 36.0 (#131)

| Benchmark | GPT-4.1 mini | Mistral Large 3 |
|---|---|---|
| LMArena Math | 1343 | 1415 |
| FrontierMath (Tiers 1-3) | 6.7% | — |
| OTIS Mock AIME 2024-2025 | 44.7% | — |
| Omni-MATH | 49.1% | — |
| MATH Level 5 | 87.3% | — |
| FrontierMath (Feb 2025 set) | 4.5% | — |

## Knowledge

- GPT-4.1 mini: 34.7 (#183)
- Mistral Large 3: 35.5 (#173)

| Benchmark | GPT-4.1 mini | Mistral Large 3 |
|---|---|---|
| LMArena Expert | 1338 | 1421 |
| GPQA Diamond | 65.8% | — |
| SimpleQA Verified | 12.7% | — |
| MMLU-Pro | 78.3% | — |
| Vectara Hallucination Rate | — | 14.5% |
| GPQA (HELM) | 61.4% | — |

## Multimodal

- GPT-4.1 mini: 35.2 (#77)
- Mistral Large 3: 37.6 (#65)

| Benchmark | GPT-4.1 mini | Mistral Large 3 |
|---|---|---|
| LMArena Vision | 1181 | 1222 |

## Multilingual

- GPT-4.1 mini: 45.9 (#161)
- Mistral Large 3: 52.6 (#79)

| Benchmark | GPT-4.1 mini | Mistral Large 3 |
|---|---|---|
| LMArena Non-English | 1318 | 1412 |
| LMArena Chinese | 1329 | 1448 |
| LMArena French | 1357 | 1456 |
| LMArena German | 1349 | 1438 |
| LMArena Japanese | 1291 | 1399 |
| LMArena Korean | 1298 | 1384 |
| LMArena Russian | 1324 | 1412 |
| LMArena Spanish | 1319 | 1437 |

## Instruction Following

- GPT-4.1 mini: 73.9 (#113)
- Mistral Large 3: 74.1 (#104)

| Benchmark | GPT-4.1 mini | Mistral Large 3 |
|---|---|---|
| LMArena Instruction Following | 1332 | 1402 |
| IFEval | 90.4% | — |

## Long Context

- GPT-4.1 mini: 31.8 (#270)
- Mistral Large 3: 43.1 (#102)

| Benchmark | GPT-4.1 mini | Mistral Large 3 |
|---|---|---|
| LMArena Longer Query | 1344 | 1413 |
| Fiction.LiveBench | 44.4% | — |

## Writing & Preference

- GPT-4.1 mini: 48.8 (#193)
- Mistral Large 3: 60.2 (#100)

| Benchmark | GPT-4.1 mini | Mistral Large 3 |
|---|---|---|
| LMArena Text | 1341 | 1427 |
| LMArena Creative Writing | 1300 | 1385 |
| EQ-Bench Creative Writing | 1147 | 1412 |
| LMArena Multi-Turn | 1354 | 1429 |
| WildBench | 83.8% | — |

## FAQ

### Is GPT-4.1 mini better than Mistral Large 3?

Mistral Large 3 is the stronger model overall, scoring 38.6 to 33.5 on the Noometry Index.

### Which is cheaper, GPT-4.1 mini or Mistral Large 3?

Mistral Large 3 is cheaper. It lists at $0.25 per million input tokens and $0.75 per million output tokens; GPT-4.1 mini lists at $0.40 and $1.60.

### Is GPT-4.1 mini or Mistral Large 3 better for coding?

Mistral Large 3 scores higher on coding benchmarks: 34.1 versus 30.4 in the Noometry coding category.

### Which has the bigger context window?

GPT-4.1 mini does, with 1.05M tokens against 262K.

### How many benchmarks do GPT-4.1 mini and Mistral Large 3 share?

20 benchmarks have published results for both models. GPT-4.1 mini has 47 scored results on Noometry and Mistral Large 3 has 24.