# Mixtral 8x22B vs Qwen3-Coder 480B-A35B Instruct

> Qwen3-Coder 480B-A35B Instruct is the stronger model overall, scoring 38.1 to 27.1 on the Noometry Index.

- Canonical page: https://noometry.com/compare/mixtral-8x22b-vs-qwen3-coder-480b-a35b-instruct
- Last updated: 2026-10-10
- Shared benchmarks: 18

## Summary

- They share 18 benchmarks with published results for both. Mixtral 8x22B scores higher in 0 categories and Qwen3-Coder 480B-A35B Instruct in 9 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3-Coder 480B-A35B Instruct leads 37.0 to 15.1.
- The biggest single-benchmark swing is WeirdML: 3.2% for Mixtral 8x22B and 41.2% for Qwen3-Coder 480B-A35B Instruct.
- Both cost about the same: $2 input and $6 output per million tokens.
- Qwen3-Coder 480B-A35B Instruct accepts more context: 262K tokens versus 64K.

## Snapshot

| | Mixtral 8x22B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 27.1 | 38.1 |
| Rank | 333 | 190 |
| Context | 64K | 262K |
| Input $/M | $2 | $1.50 |
| Output $/M | $6 | $7.50 |
| Weights | Open | Open |

## Coding

- Mixtral 8x22B: 24.2 (#329)
- Qwen3-Coder 480B-A35B Instruct: 35.5 (#223)

| Benchmark | Mixtral 8x22B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| WeirdML | 3.2% | 41.2% |
| LMArena Coding | 1166 | 1412 |
| SWE-bench Verified (bash only) | — | 55.4% |
| LMArena WebDev | — | 1275 |
| GSO | — | 4.9% |
| BigCodeBench Instruct | 40.6% | — |
| BigCodeBench Complete | 50.2% | — |
| ALE-Bench | — | 461.45 |
| AlgoTune | — | 1.44 |
| HumanEval+ | 72% | — |
| MBPP+ | 64.3% | — |

## Agentic & Tool Use

- Mixtral 8x22B: 23.1 (#127)
- Qwen3-Coder 480B-A35B Instruct: 23.9 (#123)

| Benchmark | Mixtral 8x22B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Terminal-Bench | — | 27.2% |
| Cybench | 7.5% | — |

## Reasoning

- Mixtral 8x22B: 19.9 (#248)
- Qwen3-Coder 480B-A35B Instruct: 25.5 (#149)

| Benchmark | Mixtral 8x22B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Hard Prompts | 1150 | 1372 |
| Kagi LLM Benchmark | — | 49.5% |
| DTBench | 55.1% | — |
| Epoch Capabilities Index | 122.03 | — |
| ForecastBench | 56.3 | — |

## Math

- Mixtral 8x22B: 22.9 (#275)
- Qwen3-Coder 480B-A35B Instruct: 37.6 (#150)

| Benchmark | Mixtral 8x22B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Math | 1184 | 1365 |
| Omni-MATH | 16.3% | — |
| MATH Level 5 | 24.2% | — |

## Knowledge

- Mixtral 8x22B: 15.1 (#293)
- Qwen3-Coder 480B-A35B Instruct: 37.0 (#162)

| Benchmark | Mixtral 8x22B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Expert | 1113 | 1338 |
| GPQA Diamond | 34.1% | — |
| MMLU-Pro | 46% | — |
| GPQA (HELM) | 33.4% | — |
| MMLU | 77.8% | — |

## Multilingual

- Mixtral 8x22B: 32.8 (#255)
- Qwen3-Coder 480B-A35B Instruct: 47.7 (#148)

| Benchmark | Mixtral 8x22B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Non-English | 1128 | 1346 |
| LMArena Chinese | 1116 | 1357 |
| LMArena French | 1166 | 1398 |
| LMArena German | 1141 | 1325 |
| LMArena Japanese | 1037 | 1310 |
| LMArena Korean | 1057 | 1305 |
| LMArena Russian | 1158 | 1366 |
| LMArena Spanish | 1151 | 1360 |

## Instruction Following

- Mixtral 8x22B: 57.7 (#266)
- Qwen3-Coder 480B-A35B Instruct: 71.6 (#147)

| Benchmark | Mixtral 8x22B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Instruction Following | 1147 | 1355 |
| IFEval | 72.4% | — |

## Long Context

- Mixtral 8x22B: 34.7 (#247)
- Qwen3-Coder 480B-A35B Instruct: 42.0 (#131)

| Benchmark | Mixtral 8x22B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Longer Query | 1144 | 1378 |

## Writing & Preference

- Mixtral 8x22B: 36.9 (#262)
- Qwen3-Coder 480B-A35B Instruct: 55.3 (#147)

| Benchmark | Mixtral 8x22B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Text | 1162 | 1357 |
| LMArena Creative Writing | 1141 | 1333 |
| LMArena Multi-Turn | 1130 | 1365 |
| WildBench | 71.1% | — |

## FAQ

### Is Mixtral 8x22B better than Qwen3-Coder 480B-A35B Instruct?

Qwen3-Coder 480B-A35B Instruct is the stronger model overall, scoring 38.1 to 27.1 on the Noometry Index.

### Which is cheaper, Mixtral 8x22B or Qwen3-Coder 480B-A35B Instruct?

Qwen3-Coder 480B-A35B Instruct is cheaper. It lists at $1.50 per million input tokens and $7.50 per million output tokens; Mixtral 8x22B lists at $2 and $6.

### Is Mixtral 8x22B or Qwen3-Coder 480B-A35B Instruct better for coding?

Qwen3-Coder 480B-A35B Instruct scores higher on coding benchmarks: 35.5 versus 24.2 in the Noometry coding category.

### Which has the bigger context window?

Qwen3-Coder 480B-A35B Instruct does, with 262K tokens against 64K.

### How many benchmarks do Mixtral 8x22B and Qwen3-Coder 480B-A35B Instruct share?

18 benchmarks have published results for both models. Mixtral 8x22B has 34 scored results on Noometry and Qwen3-Coder 480B-A35B Instruct has 25.