# GPT-4 Turbo vs Mixtral 8x22B

> GPT-4 Turbo is the stronger model overall, scoring 30.5 to 27.1 on the Noometry Index. Mixtral 8x22B costs 5.0× less per token, which makes it the better buy when GPT-4 Turbo's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-4-turbo-vs-mixtral-8x22b
- Last updated: 2026-10-12
- Shared benchmarks: 28

## Summary

- They share 28 benchmarks with published results for both. GPT-4 Turbo scores higher in 6 categories and Mixtral 8x22B in 2 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Mixtral 8x22B leads 22.9 to 9.0.
- The biggest single-benchmark swing is MATH Level 5: 46.7% for GPT-4 Turbo and 24.2% for Mixtral 8x22B.
- Mixtral 8x22B is cheaper at $2 / $6 per million input/output tokens, against $10 / $30 for GPT-4 Turbo.
- GPT-4 Turbo accepts more context: 128K tokens versus 64K.
- Mixtral 8x22B has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-4 Turbo | Mixtral 8x22B |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 30.5 | 27.1 |
| Rank | 292 | 333 |
| Context | 128K | 64K |
| Input $/M | $10 | $2 |
| Output $/M | $30 | $6 |
| Weights | Proprietary | Open |

## Coding

- GPT-4 Turbo: 33.8 (#249)
- Mixtral 8x22B: 24.2 (#329)

| Benchmark | GPT-4 Turbo | Mixtral 8x22B |
|---|---|---|
| WeirdML | 18% | 3.2% |
| BigCodeBench Instruct | 48.2% | 40.6% |
| LMArena Coding | 1268 | 1166 |
| BigCodeBench Complete | 58.2% | 50.2% |
| HumanEval+ | 86.6% | 72% |
| MBPP+ | 73.3% | 64.3% |

## Agentic & Tool Use

- GPT-4 Turbo: —
- Mixtral 8x22B: 23.1 (#127)

| Benchmark | GPT-4 Turbo | Mixtral 8x22B |
|---|---|---|
| Cybench | — | 7.5% |
| METR Time Horizons | 36.7% | — |

## Reasoning

- GPT-4 Turbo: 15.3 (#317)
- Mixtral 8x22B: 19.9 (#248)

| Benchmark | GPT-4 Turbo | Mixtral 8x22B |
|---|---|---|
| LMArena Hard Prompts | 1251 | 1150 |
| DTBench | 61.6% | 55.1% |
| Epoch Capabilities Index | 127.25 | 122.03 |
| ForecastBench | 59.4 | 56.3 |
| SimpleBench | 25.1% | — |
| Chess Puzzles | 6% | — |
| LMCA | 9.8% | — |

## Math

- GPT-4 Turbo: 9.0 (#322)
- Mixtral 8x22B: 22.9 (#275)

| Benchmark | GPT-4 Turbo | Mixtral 8x22B |
|---|---|---|
| LMArena Math | 1272 | 1184 |
| MATH Level 5 | 46.7% | 24.2% |
| FrontierMath (Tiers 1-3) | 0.7% | — |
| OTIS Mock AIME 2024-2025 | 6.7% | — |
| Omni-MATH | — | 16.3% |

## Knowledge

- GPT-4 Turbo: 24.3 (#268)
- Mixtral 8x22B: 15.1 (#293)

| Benchmark | GPT-4 Turbo | Mixtral 8x22B |
|---|---|---|
| GPQA Diamond | 46.6% | 34.1% |
| LMArena Expert | 1223 | 1113 |
| MMLU | 81.3% | 77.8% |
| MMLU-Pro | — | 46% |
| Confabulations | 28.4% | — |
| GPQA (HELM) | — | 33.4% |

## Multimodal

- GPT-4 Turbo: 30.6 (#110)
- Mixtral 8x22B: —

| Benchmark | GPT-4 Turbo | Mixtral 8x22B |
|---|---|---|
| LMArena Vision | 1090 | — |

## Multilingual

- GPT-4 Turbo: 40.5 (#216)
- Mixtral 8x22B: 32.8 (#255)

| Benchmark | GPT-4 Turbo | Mixtral 8x22B |
|---|---|---|
| LMArena Non-English | 1245 | 1128 |
| LMArena Chinese | 1242 | 1116 |
| LMArena French | 1276 | 1166 |
| LMArena German | 1259 | 1141 |
| LMArena Japanese | 1194 | 1037 |
| LMArena Korean | 1187 | 1057 |
| LMArena Russian | 1259 | 1158 |
| LMArena Spanish | 1260 | 1151 |

## Instruction Following

- GPT-4 Turbo: 65.8 (#216)
- Mixtral 8x22B: 57.7 (#266)

| Benchmark | GPT-4 Turbo | Mixtral 8x22B |
|---|---|---|
| LMArena Instruction Following | 1249 | 1147 |
| IFEval | — | 72.4% |

## Long Context

- GPT-4 Turbo: 38.0 (#206)
- Mixtral 8x22B: 34.7 (#247)

| Benchmark | GPT-4 Turbo | Mixtral 8x22B |
|---|---|---|
| LMArena Longer Query | 1254 | 1144 |

## Writing & Preference

- GPT-4 Turbo: 47.7 (#206)
- Mixtral 8x22B: 36.9 (#262)

| Benchmark | GPT-4 Turbo | Mixtral 8x22B |
|---|---|---|
| LMArena Text | 1272 | 1162 |
| LMArena Creative Writing | 1269 | 1141 |
| LMArena Multi-Turn | 1267 | 1130 |
| WildBench | — | 71.1% |

## FAQ

### Is GPT-4 Turbo better than Mixtral 8x22B?

GPT-4 Turbo is the stronger model overall, scoring 30.5 to 27.1 on the Noometry Index. Mixtral 8x22B costs 5.0× less per token, which makes it the better buy when GPT-4 Turbo's lead doesn't matter for your workload.

### Which is cheaper, GPT-4 Turbo or Mixtral 8x22B?

Mixtral 8x22B is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; GPT-4 Turbo lists at $10 and $30.

### Is GPT-4 Turbo or Mixtral 8x22B better for coding?

GPT-4 Turbo scores higher on coding benchmarks: 33.8 versus 24.2 in the Noometry coding category.

### Which has the bigger context window?

GPT-4 Turbo does, with 128K tokens against 64K.

### How many benchmarks do GPT-4 Turbo and Mixtral 8x22B share?

28 benchmarks have published results for both models. GPT-4 Turbo has 36 scored results on Noometry and Mixtral 8x22B has 34.