# Claude Sonnet 4.6 vs Mixtral 8x22B

> Claude Sonnet 4.6 is the stronger model overall, scoring 50.1 to 26.7 on the Noometry Index. Mixtral 8x22B costs 2.0× less per token, which makes it the better buy when Claude Sonnet 4.6's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/claude-sonnet-4-6-vs-mixtral-8x22b
- Last updated: 2026-10-10
- Shared benchmarks: 22

## Summary

- They share 22 benchmarks with published results for both. Claude Sonnet 4.6 scores higher in 9 categories and Mixtral 8x22B in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Claude Sonnet 4.6 leads 51.6 to 15.1.
- The biggest single-benchmark swing is WeirdML: 66.1% for Claude Sonnet 4.6 and 3.2% for Mixtral 8x22B.
- Mixtral 8x22B is cheaper at $2 / $6 per million input/output tokens, against $3 / $15 for Claude Sonnet 4.6.
- Claude Sonnet 4.6 accepts more context: 1M tokens versus 64K.
- Mixtral 8x22B has downloadable open weights; the other is API-only.

## Snapshot

| | Claude Sonnet 4.6 | Mixtral 8x22B |
|---|---|---|
| Provider | Anthropic | Mistral AI |
| Noometry Index | 50.1 | 26.7 |
| Rank | 42 | 330 |
| Context | 1M | 64K |
| Input $/M | $3 | $2 |
| Output $/M | $15 | $6 |
| Weights | Proprietary | Open |

## Coding

- Claude Sonnet 4.6: 46.0 (#62)
- Mixtral 8x22B: 23.8 (#324)

| Benchmark | Claude Sonnet 4.6 | Mixtral 8x22B |
|---|---|---|
| WeirdML | 66.1% | 3.2% |
| LMArena Coding | 1504 | 1166 |
| SWE-bench Verified | 75.2% | — |
| DeepSWE | 29.9% | — |
| FrontierCode | 24.3% | — |
| LMArena WebDev | 1521 | — |
| SciCode | 46.8% | — |
| BigCodeBench Instruct | — | 40.6% |
| BigCodeBench Complete | — | 50.2% |
| ALE-Bench | 1,327 | — |
| HumanEval+ | — | 72% |
| MBPP+ | — | 64.3% |

## Agentic & Tool Use

- Claude Sonnet 4.6: 39.1 (#26)
- Mixtral 8x22B: 22.8 (#119)

| Benchmark | Claude Sonnet 4.6 | Mixtral 8x22B |
|---|---|---|
| Terminal-Bench | 53.4% | — |
| APEX-Agents | 43% | — |
| OSWorld 2.0 | 9.3% | — |
| Cybench | — | 7.5% |
| DeepResearch Bench | 54.9% | — |
| OSWorld | 72.1% | — |
| ExploitBench | 23.6% | — |
| GBAEval | 48.8% | — |
| GDP.pdf | 18% | — |
| LMArena Search | 1221 | — |
| Vending-Bench 2 | 7,204 | — |

## Reasoning

- Claude Sonnet 4.6: 46.1 (#40)
- Mixtral 8x22B: 19.1 (#246)

| Benchmark | Claude Sonnet 4.6 | Mixtral 8x22B |
|---|---|---|
| LMArena Hard Prompts | 1485 | 1150 |
| DTBench | 89.9% | 55.1% |
| Epoch Capabilities Index | 152.25 | 122 |
| ForecastBench | 62 | 56.3 |
| ARC-AGI-2 | 60.4% | — |
| NYT Connections (extended) | 80.9% | — |
| ARC-AGI-1 | 86.5% | — |
| CritPt | 3.1% | — |
| Chess Puzzles | 13% | — |
| Thematic Generalization | 76.3% | — |
| Mystery Game Puzzles | 16% | — |
| LMCA | 46.5% | — |

## Math

- Claude Sonnet 4.6: 51.9 (#41)
- Mixtral 8x22B: 21.2 (#271)

| Benchmark | Claude Sonnet 4.6 | Mixtral 8x22B |
|---|---|---|
| LMArena Math | 1463 | 1184 |
| OTIS Mock AIME 2024-2025 | 85.8% | — |
| ProofBench | 45% | — |
| Omni-MATH | — | 16.3% |
| MATH Level 5 | — | 24.2% |
| FrontierMath (Feb 2025 set) | 32.4% | — |
| FrontierMath Tier 4 (v1) | 8.3% | — |

## Knowledge

- Claude Sonnet 4.6: 51.6 (#60)
- Mixtral 8x22B: 15.1 (#288)

| Benchmark | Claude Sonnet 4.6 | Mixtral 8x22B |
|---|---|---|
| GPQA Diamond | 87.4% | 34.1% |
| LMArena Expert | 1500 | 1113 |
| SimpleQA Verified | 35.5% | — |
| MMLU-Pro | — | 46% |
| Vectara Hallucination Rate | 10.6% | — |
| GPQA (HELM) | — | 33.4% |
| MMLU | — | 77.8% |

## Multimodal

- Claude Sonnet 4.6: 38.0 (#61)
- Mixtral 8x22B: —

| Benchmark | Claude Sonnet 4.6 | Mixtral 8x22B |
|---|---|---|
| LMArena Vision | 1283 | — |
| Blueprint-Bench 2 | 6.7% | — |
| LMArena Document | 1482 | — |

## Multilingual

- Claude Sonnet 4.6: 54.6 (#39)
- Mixtral 8x22B: 32.9 (#250)

| Benchmark | Claude Sonnet 4.6 | Mixtral 8x22B |
|---|---|---|
| LMArena Non-English | 1440 | 1128 |
| LMArena Chinese | 1491 | 1116 |
| LMArena French | 1465 | 1165 |
| LMArena German | 1428 | 1141 |
| LMArena Japanese | 1419 | 1037 |
| LMArena Korean | 1411 | 1056 |
| LMArena Russian | 1440 | 1158 |
| LMArena Spanish | 1465 | 1150 |

## Instruction Following

- Claude Sonnet 4.6: 77.6 (#23)
- Mixtral 8x22B: 57.9 (#261)

| Benchmark | Claude Sonnet 4.6 | Mixtral 8x22B |
|---|---|---|
| LMArena Instruction Following | 1476 | 1147 |
| IFEval | — | 72.4% |

## Long Context

- Claude Sonnet 4.6: 45.3 (#40)
- Mixtral 8x22B: 34.6 (#242)

| Benchmark | Claude Sonnet 4.6 | Mixtral 8x22B |
|---|---|---|
| LMArena Longer Query | 1479 | 1144 |

## Writing & Preference

- Claude Sonnet 4.6: 70.4 (#22)
- Mixtral 8x22B: 37.1 (#257)

| Benchmark | Claude Sonnet 4.6 | Mixtral 8x22B |
|---|---|---|
| LMArena Text | 1458 | 1162 |
| LMArena Creative Writing | 1435 | 1141 |
| LMArena Multi-Turn | 1464 | 1130 |
| EQ-Bench Creative Writing | 1810 | — |
| WildBench | — | 71.1% |
| EQ-Bench 4 | 1207 | — |

## FAQ

### Is Claude Sonnet 4.6 better than Mixtral 8x22B?

Claude Sonnet 4.6 is the stronger model overall, scoring 50.1 to 26.7 on the Noometry Index. Mixtral 8x22B costs 2.0× less per token, which makes it the better buy when Claude Sonnet 4.6's lead doesn't matter for your workload.

### Which is cheaper, Claude Sonnet 4.6 or Mixtral 8x22B?

Mixtral 8x22B is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; Claude Sonnet 4.6 lists at $3 and $15.

### Is Claude Sonnet 4.6 or Mixtral 8x22B better for coding?

Claude Sonnet 4.6 scores higher on coding benchmarks: 46.0 versus 23.8 in the Noometry coding category.

### Which has the bigger context window?

Claude Sonnet 4.6 does, with 1M tokens against 64K.

### How many benchmarks do Claude Sonnet 4.6 and Mixtral 8x22B share?

22 benchmarks have published results for both models. Claude Sonnet 4.6 has 57 scored results on Noometry and Mixtral 8x22B has 34.