# GPT-4.1 vs Mixtral 8x22B

> GPT-4.1 is the stronger model overall, scoring 35.9 to 27.1 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gpt-4-1-vs-mixtral-8x22b
- Last updated: 2026-10-10
- Shared benchmarks: 28

## Summary

- They share 28 benchmarks with published results for both. GPT-4.1 scores higher in 7 categories and Mixtral 8x22B in 2 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GPT-4.1 leads 37.1 to 15.1.
- The biggest single-benchmark swing is MATH Level 5: 83% for GPT-4.1 and 24.2% for Mixtral 8x22B.
- Mixtral 8x22B is cheaper at $2 / $6 per million input/output tokens, against $2 / $8 for GPT-4.1.
- GPT-4.1 accepts more context: 1.05M tokens versus 64K.
- Mixtral 8x22B has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-4.1 | Mixtral 8x22B |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 35.9 | 27.1 |
| Rank | 219 | 333 |
| Context | 1.05M | 64K |
| Input $/M | $2 | $2 |
| Output $/M | $8 | $6 |
| Weights | Proprietary | Open |

## Coding

- GPT-4.1: 34.4 (#238)
- Mixtral 8x22B: 24.2 (#329)

| Benchmark | GPT-4.1 | Mixtral 8x22B |
|---|---|---|
| WeirdML | 39% | 3.2% |
| LMArena Coding | 1391 | 1166 |
| SWE-bench Verified | 48.5% | — |
| SWE-bench Verified (bash only) | 39.6% | — |
| Aider Polyglot | 52.4% | — |
| BigCodeBench Instruct | — | 40.6% |
| BigCodeBench Complete | — | 50.2% |
| CadEval | 42% | — |
| ALE-Bench | 558.1 | — |
| HumanEval+ | — | 72% |
| MBPP+ | — | 64.3% |

## Agentic & Tool Use

- GPT-4.1: 34.7 (#43)
- Mixtral 8x22B: 23.1 (#127)

| Benchmark | GPT-4.1 | Mixtral 8x22B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 54% | — |
| Cybench | — | 7.5% |

## Reasoning

- GPT-4.1: 11.7 (#339)
- Mixtral 8x22B: 19.9 (#248)

| Benchmark | GPT-4.1 | Mixtral 8x22B |
|---|---|---|
| LMArena Hard Prompts | 1384 | 1150 |
| DTBench | 68.3% | 55.1% |
| Epoch Capabilities Index | 136.78 | 122.03 |
| ForecastBench | 61.5 | 56.3 |
| ARC-AGI-2 | 0.4% | — |
| SimpleBench | 27% | — |
| Kagi LLM Benchmark | 52.3% | — |
| ARC-AGI-1 | 5.5% | — |
| Chess Puzzles | 6% | — |
| EnigmaEval | 2.2% | — |
| LMCA | 25.6% | — |

## Math

- GPT-4.1: 22.3 (#280)
- Mixtral 8x22B: 22.9 (#275)

| Benchmark | GPT-4.1 | Mixtral 8x22B |
|---|---|---|
| Omni-MATH | 47.1% | 16.3% |
| LMArena Math | 1370 | 1184 |
| MATH Level 5 | 83% | 24.2% |
| FrontierMath (Tiers 1-3) | 6% | — |
| OTIS Mock AIME 2024-2025 | 38.3% | — |
| FrontierMath (Feb 2025 set) | 5.5% | — |
| FrontierMath Tier 4 (v1) | 0% | — |

## Knowledge

- GPT-4.1: 37.1 (#160)
- Mixtral 8x22B: 15.1 (#293)

| Benchmark | GPT-4.1 | Mixtral 8x22B |
|---|---|---|
| GPQA Diamond | 66.9% | 34.1% |
| MMLU-Pro | 81.1% | 46% |
| GPQA (HELM) | 65.9% | 33.4% |
| LMArena Expert | 1364 | 1113 |
| Humanity's Last Exam | 5.4% | — |
| SimpleQA Verified | 31.1% | — |
| Vectara Hallucination Rate | 5.6% | — |
| MMLU | — | 77.8% |

## Multimodal

- GPT-4.1: 38.2 (#67)
- Mixtral 8x22B: —

| Benchmark | GPT-4.1 | Mixtral 8x22B |
|---|---|---|
| LMArena Vision | 1211 | — |
| GeoBench | 72% | — |

## Multilingual

- GPT-4.1: 49.4 (#133)
- Mixtral 8x22B: 32.8 (#255)

| Benchmark | GPT-4.1 | Mixtral 8x22B |
|---|---|---|
| LMArena Non-English | 1370 | 1128 |
| LMArena Chinese | 1382 | 1116 |
| LMArena French | 1382 | 1166 |
| LMArena German | 1381 | 1141 |
| LMArena Japanese | 1319 | 1037 |
| LMArena Korean | 1339 | 1057 |
| LMArena Russian | 1377 | 1158 |
| LMArena Spanish | 1376 | 1151 |

## Instruction Following

- GPT-4.1: 71.3 (#153)
- Mixtral 8x22B: 57.7 (#266)

| Benchmark | GPT-4.1 | Mixtral 8x22B |
|---|---|---|
| IFEval | 83.8% | 72.4% |
| LMArena Instruction Following | 1367 | 1147 |

## Long Context

- GPT-4.1: 40.0 (#163)
- Mixtral 8x22B: 34.7 (#247)

| Benchmark | GPT-4.1 | Mixtral 8x22B |
|---|---|---|
| LMArena Longer Query | 1385 | 1144 |
| Fiction.LiveBench | 63.9% | — |

## Writing & Preference

- GPT-4.1: 57.6 (#125)
- Mixtral 8x22B: 36.9 (#262)

| Benchmark | GPT-4.1 | Mixtral 8x22B |
|---|---|---|
| LMArena Text | 1383 | 1162 |
| LMArena Creative Writing | 1363 | 1141 |
| WildBench | 85.4% | 71.1% |
| LMArena Multi-Turn | 1398 | 1130 |
| EQ-Bench Creative Writing | 1420 | — |

## FAQ

### Is GPT-4.1 better than Mixtral 8x22B?

GPT-4.1 is the stronger model overall, scoring 35.9 to 27.1 on the Noometry Index.

### Which is cheaper, GPT-4.1 or Mixtral 8x22B?

Mixtral 8x22B is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; GPT-4.1 lists at $2 and $8.

### Is GPT-4.1 or Mixtral 8x22B better for coding?

GPT-4.1 scores higher on coding benchmarks: 34.4 versus 24.2 in the Noometry coding category.

### Which has the bigger context window?

GPT-4.1 does, with 1.05M tokens against 64K.

### How many benchmarks do GPT-4.1 and Mixtral 8x22B share?

28 benchmarks have published results for both models. GPT-4.1 has 52 scored results on Noometry and Mixtral 8x22B has 34.