# GPT-4.1 nano vs Mistral 7B

> GPT-4.1 nano is the stronger model overall, scoring 27.9 to 23.0 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gpt-4-1-nano-vs-mistral-7b
- Last updated: 2026-10-12
- Shared benchmarks: 19

## Summary

- They share 19 benchmarks with published results for both. GPT-4.1 nano scores higher in 5 categories and Mistral 7B in 3 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-4.1 nano leads 26.9 to 8.1.
- The biggest single-benchmark swing is MATH Level 5: 70% for GPT-4.1 nano and 3.7% for Mistral 7B.
- GPT-4.1 nano is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.25 / $0.25 for Mistral 7B.
- GPT-4.1 nano accepts more context: 1.05M tokens versus 8K.
- Mistral 7B has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-4.1 nano | Mistral 7B |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 27.9 | 23.0 |
| Rank | 327 | 351 |
| Context | 1.05M | 8K |
| Input $/M | $0.10 | $0.25 |
| Output $/M | $0.40 | $0.25 |
| Weights | Proprietary | Open |

## Coding

- GPT-4.1 nano: 24.1 (#330)
- Mistral 7B: 26.4 (#326)

| Benchmark | GPT-4.1 nano | Mistral 7B |
|---|---|---|
| LMArena Coding | 1306 | 1082 |
| Aider Polyglot | 8.9% | — |
| SciCode | 25.9% | — |
| WeirdML | 19% | — |
| BigCodeBench Instruct | — | 19.5% |
| BigCodeBench Complete | — | 27.3% |
| HumanEval+ | — | 36% |
| MBPP+ | — | 42.1% |

## Agentic & Tool Use

- GPT-4.1 nano: 26.5 (#104)
- Mistral 7B: —

| Benchmark | GPT-4.1 nano | Mistral 7B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 33% | — |

## Reasoning

- GPT-4.1 nano: 8.5 (#349)
- Mistral 7B: 13.1 (#336)

| Benchmark | GPT-4.1 nano | Mistral 7B |
|---|---|---|
| LMArena Hard Prompts | 1286 | 1067 |
| DTBench | 52.5% | 42.5% |
| Epoch Capabilities Index | 129.62 | 112.21 |
| ARC-AGI-2 | 0% | — |
| Kagi LLM Benchmark | 33.3% | — |
| ARC-AGI-1 | 0% | — |
| CritPt | 0% | — |
| Chess Puzzles | — | 0% |
| LMCA | 5.5% | — |
| Adversarial NLI | — | 47.1% |
| BIG-Bench Hard | — | 56.1% |
| HellaSwag | — | 81% |
| PIQA | — | 83% |
| WinoGrande | — | 75.3% |

## Math

- GPT-4.1 nano: 26.9 (#252)
- Mistral 7B: 8.1 (#325)

| Benchmark | GPT-4.1 nano | Mistral 7B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 28.9% | 0.3% |
| LMArena Math | 1274 | 1085 |
| MATH Level 5 | 70% | 3.7% |
| Omni-MATH | 36.7% | — |
| FrontierMath (Feb 2025 set) | 1% | — |
| GSM8K | — | 54.4% |

## Knowledge

- GPT-4.1 nano: 21.8 (#273)
- Mistral 7B: 7.4 (#311)

| Benchmark | GPT-4.1 nano | Mistral 7B |
|---|---|---|
| GPQA Diamond | 48.9% | 15.2% |
| LMArena Expert | 1272 | 1036 |
| SimpleQA Verified | 6% | — |
| MMLU-Pro | 55% | — |
| GPQA (HELM) | 50.7% | — |
| ARC (AI2) Challenge | — | 78.6% |
| BoolQ | — | 87.4% |
| MMLU | — | 62.5% |
| OpenBookQA | — | 79.8% |
| TriviaQA | — | 75.2% |

## Multimodal

- GPT-4.1 nano: 29.2 (#113)
- Mistral 7B: —

| Benchmark | GPT-4.1 nano | Mistral 7B |
|---|---|---|
| LMArena Vision | 1063 | — |

## Multilingual

- GPT-4.1 nano: 41.6 (#205)
- Mistral 7B: 25.8 (#283)

| Benchmark | GPT-4.1 nano | Mistral 7B |
|---|---|---|
| LMArena Non-English | 1260 | 1012 |
| LMArena Chinese | 1270 | 1009 |
| LMArena German | 1288 | 987 |
| LMArena Japanese | 1198 | 878 |
| LMArena Russian | 1261 | 1018 |
| LMArena French | — | 1037 |
| LMArena Spanish | — | 1026 |

## Instruction Following

- GPT-4.1 nano: 67.8 (#193)
- Mistral 7B: 54.2 (#280)

| Benchmark | GPT-4.1 nano | Mistral 7B |
|---|---|---|
| LMArena Instruction Following | 1267 | 1060 |
| IFEval | 84.3% | — |

## Long Context

- GPT-4.1 nano: 23.7 (#296)
- Mistral 7B: 32.2 (#271)

| Benchmark | GPT-4.1 nano | Mistral 7B |
|---|---|---|
| LMArena Longer Query | 1283 | 1060 |
| Fiction.LiveBench | 25% | — |

## Writing & Preference

- GPT-4.1 nano: 40.5 (#243)
- Mistral 7B: 30.7 (#286)

| Benchmark | GPT-4.1 nano | Mistral 7B |
|---|---|---|
| LMArena Text | 1285 | 1090 |
| LMArena Creative Writing | 1260 | 1068 |
| LMArena Multi-Turn | 1277 | 1062 |
| EQ-Bench Creative Writing | 946 | — |
| WildBench | 81.2% | — |

## FAQ

### Is GPT-4.1 nano better than Mistral 7B?

GPT-4.1 nano is the stronger model overall, scoring 27.9 to 23.0 on the Noometry Index.

### Which is cheaper, GPT-4.1 nano or Mistral 7B?

GPT-4.1 nano is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Mistral 7B lists at $0.25 and $0.25.

### Is GPT-4.1 nano or Mistral 7B better for coding?

Mistral 7B scores higher on coding benchmarks: 26.4 versus 24.1 in the Noometry coding category.

### Which has the bigger context window?

GPT-4.1 nano does, with 1.05M tokens against 8K.

### How many benchmarks do GPT-4.1 nano and Mistral 7B share?

19 benchmarks have published results for both models. GPT-4.1 nano has 38 scored results on Noometry and Mistral 7B has 37.