# DeepSeek-V3.1 vs Mixtral 8x22B

> DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 26.7 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v3-1-vs-mixtral-8x22b
- Last updated: 2026-10-10
- Shared benchmarks: 21

## Summary

- They share 21 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 8 categories and Mixtral 8x22B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where DeepSeek-V3.1 leads 43.0 to 15.1.
- The biggest single-benchmark swing is WeirdML: 38.4% for DeepSeek-V3.1 and 3.2% for Mixtral 8x22B.
- DeepSeek-V3.1 is cheaper at $0.25 / $0.95 per million input/output tokens, against $2 / $6 for Mixtral 8x22B.
- DeepSeek-V3.1 accepts more context: 164K tokens versus 64K.

## Snapshot

| | DeepSeek-V3.1 | Mixtral 8x22B |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 42.2 | 26.7 |
| Rank | 106 | 330 |
| Context | 164K | 64K |
| Input $/M | $0.25 | $2 |
| Output $/M | $0.95 | $6 |
| Weights | Open | Open |

## Coding

- DeepSeek-V3.1: 39.8 (#140)
- Mixtral 8x22B: 23.8 (#324)

| Benchmark | DeepSeek-V3.1 | Mixtral 8x22B |
|---|---|---|
| WeirdML | 38.4% | 3.2% |
| LMArena Coding | 1417 | 1166 |
| BigCodeBench Instruct | — | 40.6% |
| BigCodeBench Complete | — | 50.2% |
| HumanEval+ | — | 72% |
| MBPP+ | — | 64.3% |

## Agentic & Tool Use

- DeepSeek-V3.1: —
- Mixtral 8x22B: 22.8 (#119)

| Benchmark | DeepSeek-V3.1 | Mixtral 8x22B |
|---|---|---|
| Cybench | — | 7.5% |

## Reasoning

- DeepSeek-V3.1: 27.3 (#109)
- Mixtral 8x22B: 19.1 (#246)

| Benchmark | DeepSeek-V3.1 | Mixtral 8x22B |
|---|---|---|
| LMArena Hard Prompts | 1417 | 1150 |
| DTBench | 82.7% | 55.1% |
| Epoch Capabilities Index | 139.92 | 122 |
| ForecastBench | 58 | 56.3 |
| SimpleBench | 40% | — |
| Kagi LLM Benchmark | 53.2% | — |
| LMCA | 24.3% | — |

## Math

- DeepSeek-V3.1: 36.1 (#125)
- Mixtral 8x22B: 21.2 (#271)

| Benchmark | DeepSeek-V3.1 | Mixtral 8x22B |
|---|---|---|
| LMArena Math | 1420 | 1184 |
| Omni-MATH | — | 16.3% |
| MATH Level 5 | — | 24.2% |

## Knowledge

- DeepSeek-V3.1: 43.0 (#86)
- Mixtral 8x22B: 15.1 (#288)

| Benchmark | DeepSeek-V3.1 | Mixtral 8x22B |
|---|---|---|
| LMArena Expert | 1403 | 1113 |
| GPQA Diamond | — | 34.1% |
| MMLU-Pro | — | 46% |
| Vectara Hallucination Rate | 5.5% | — |
| GPQA (HELM) | — | 33.4% |
| MMLU | — | 77.8% |

## Multilingual

- DeepSeek-V3.1: 51.8 (#100)
- Mixtral 8x22B: 32.9 (#250)

| Benchmark | DeepSeek-V3.1 | Mixtral 8x22B |
|---|---|---|
| LMArena Non-English | 1400 | 1128 |
| LMArena Chinese | 1470 | 1116 |
| LMArena French | 1447 | 1165 |
| LMArena German | 1412 | 1141 |
| LMArena Japanese | 1374 | 1037 |
| LMArena Korean | 1337 | 1056 |
| LMArena Russian | 1405 | 1158 |
| LMArena Spanish | 1429 | 1150 |

## Instruction Following

- DeepSeek-V3.1: 74.1 (#105)
- Mixtral 8x22B: 57.9 (#261)

| Benchmark | DeepSeek-V3.1 | Mixtral 8x22B |
|---|---|---|
| LMArena Instruction Following | 1400 | 1147 |
| IFEval | — | 72.4% |

## Long Context

- DeepSeek-V3.1: 36.3 (#227)
- Mixtral 8x22B: 34.6 (#242)

| Benchmark | DeepSeek-V3.1 | Mixtral 8x22B |
|---|---|---|
| LMArena Longer Query | 1422 | 1144 |
| Fiction.LiveBench | 52.8% | — |

## Writing & Preference

- DeepSeek-V3.1: 60.5 (#93)
- Mixtral 8x22B: 37.1 (#257)

| Benchmark | DeepSeek-V3.1 | Mixtral 8x22B |
|---|---|---|
| LMArena Text | 1420 | 1162 |
| LMArena Creative Writing | 1401 | 1141 |
| LMArena Multi-Turn | 1408 | 1130 |
| EQ-Bench Creative Writing | 1436 | — |
| WildBench | — | 71.1% |

## FAQ

### Is DeepSeek-V3.1 better than Mixtral 8x22B?

DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 26.7 on the Noometry Index.

### Which is cheaper, DeepSeek-V3.1 or Mixtral 8x22B?

DeepSeek-V3.1 is cheaper. It lists at $0.25 per million input tokens and $0.95 per million output tokens; Mixtral 8x22B lists at $2 and $6.

### Is DeepSeek-V3.1 or Mixtral 8x22B better for coding?

DeepSeek-V3.1 scores higher on coding benchmarks: 39.8 versus 23.8 in the Noometry coding category.

### Which has the bigger context window?

DeepSeek-V3.1 does, with 164K tokens against 64K.

### How many benchmarks do DeepSeek-V3.1 and Mixtral 8x22B share?

21 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and Mixtral 8x22B has 34.