# DeepSeek V4.1 Flash vs Mixtral 8x7B

> DeepSeek V4.1 Flash is the stronger model overall, scoring 52.8 to 27.1 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v4-1-flash-vs-mixtral-8x7b
- Last updated: 2026-10-12
- Shared benchmarks: 20

## Summary

- They share 20 benchmarks with published results for both. DeepSeek V4.1 Flash scores higher in 8 categories and Mixtral 8x7B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where DeepSeek V4.1 Flash leads 66.7 to 18.8.
- The biggest single-benchmark swing is GPQA Diamond: 89.8% for DeepSeek V4.1 Flash and 30.6% for Mixtral 8x7B.
- DeepSeek V4.1 Flash is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.70 / $0.70 for Mixtral 8x7B.
- DeepSeek V4.1 Flash accepts more context: 1M tokens versus 32K.

## Snapshot

| | DeepSeek V4.1 Flash | Mixtral 8x7B |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 52.8 | 27.1 |
| Rank | 38 | 334 |
| Context | 1M | 32K |
| Input $/M | $0.15 | $0.70 |
| Output $/M | $0.60 | $0.70 |
| Weights | Open | Open |

## Coding

- DeepSeek V4.1 Flash: 52.9 (#32)
- Mixtral 8x7B: 32.8 (#269)

| Benchmark | DeepSeek V4.1 Flash | Mixtral 8x7B |
|---|---|---|
| LMArena Coding | 1506 | 1126 |
| LMArena WebDev | 1619 | — |
| SciCode | 51.9% | — |
| ALE-Bench | 1,092 | — |
| HumanEval+ | — | 39.6% |
| MBPP+ | — | 49.7% |

## Agentic & Tool Use

- DeepSeek V4.1 Flash: 31.2 (#69)
- Mixtral 8x7B: —

| Benchmark | DeepSeek V4.1 Flash | Mixtral 8x7B |
|---|---|---|
| APEX-Agents | 39.5% | — |
| GDP.pdf | 19.8% | — |

## Reasoning

- DeepSeek V4.1 Flash: 50.2 (#36)
- Mixtral 8x7B: 18.2 (#285)

| Benchmark | DeepSeek V4.1 Flash | Mixtral 8x7B |
|---|---|---|
| LMArena Hard Prompts | 1483 | 1115 |
| DTBench | 89.9% | 49.6% |
| Epoch Capabilities Index | 154.9 | 118.47 |
| NYT Connections (extended) | 89.6% | — |
| CritPt | 14.3% | — |
| Mystery Game Puzzles | 43% | — |
| LMCA | 47% | — |
| Surface Evolver Bench | 46.3% | — |
| Adversarial NLI | — | 55.2% |
| ForecastBench | — | 56.3 |
| HellaSwag | — | 86.7% |
| PIQA | — | 83.6% |
| WinoGrande | — | 77.2% |

## Math

- DeepSeek V4.1 Flash: 66.7 (#25)
- Mixtral 8x7B: 18.8 (#289)

| Benchmark | DeepSeek V4.1 Flash | Mixtral 8x7B |
|---|---|---|
| LMArena Math | 1477 | 1147 |
| FrontierMath (Tiers 1-3) | 67.4% | — |
| FrontierMath Tier 4 | 26.8% | — |
| OTIS Mock AIME 2024-2025 | 98.3% | — |
| ProofBench | 54% | — |
| Omni-MATH | — | 10.5% |
| MATH Level 5 | — | 10% |
| GSM8K | — | 74.4% |

## Knowledge

- DeepSeek V4.1 Flash: 57.9 (#38)
- Mixtral 8x7B: 11.0 (#301)

| Benchmark | DeepSeek V4.1 Flash | Mixtral 8x7B |
|---|---|---|
| GPQA Diamond | 89.8% | 30.6% |
| LMArena Expert | 1506 | 1088 |
| MMLU-Pro | — | 33.5% |
| GPQA (HELM) | — | 29.6% |
| ARC (AI2) Challenge | — | 87.3% |
| MMLU | — | 70.6% |
| OpenBookQA | — | 85.8% |
| TriviaQA | — | 82.2% |

## Multimodal

- DeepSeek V4.1 Flash: 39.1 (#61)
- Mixtral 8x7B: —

| Benchmark | DeepSeek V4.1 Flash | Mixtral 8x7B |
|---|---|---|
| LMArena Vision | 1277 | — |
| Furniture Assembly | 34.2% | — |

## Multilingual

- DeepSeek V4.1 Flash: 55.0 (#35)
- Mixtral 8x7B: 29.6 (#266)

| Benchmark | DeepSeek V4.1 Flash | Mixtral 8x7B |
|---|---|---|
| LMArena Non-English | 1448 | 1077 |
| LMArena Chinese | 1497 | 1055 |
| LMArena French | 1452 | 1166 |
| LMArena German | 1484 | 1114 |
| LMArena Japanese | 1412 | 931 |
| LMArena Korean | 1452 | 968 |
| LMArena Russian | 1471 | 1090 |
| LMArena Spanish | 1459 | 1111 |

## Instruction Following

- DeepSeek V4.1 Flash: 77.3 (#26)
- Mixtral 8x7B: 51.0 (#297)

| Benchmark | DeepSeek V4.1 Flash | Mixtral 8x7B |
|---|---|---|
| LMArena Instruction Following | 1474 | 1109 |
| IFEval | — | 57.5% |

## Long Context

- DeepSeek V4.1 Flash: 45.2 (#47)
- Mixtral 8x7B: 33.4 (#260)

| Benchmark | DeepSeek V4.1 Flash | Mixtral 8x7B |
|---|---|---|
| LMArena Longer Query | 1475 | 1103 |

## Writing & Preference

- DeepSeek V4.1 Flash: 65.4 (#48)
- Mixtral 8x7B: 34.2 (#270)

| Benchmark | DeepSeek V4.1 Flash | Mixtral 8x7B |
|---|---|---|
| LMArena Text | 1462 | 1132 |
| LMArena Creative Writing | 1435 | 1109 |
| LMArena Multi-Turn | 1457 | 1115 |
| EQ-Bench Creative Writing | 1540 | — |
| WildBench | — | 67.3% |

## FAQ

### Is DeepSeek V4.1 Flash better than Mixtral 8x7B?

DeepSeek V4.1 Flash is the stronger model overall, scoring 52.8 to 27.1 on the Noometry Index.

### Which is cheaper, DeepSeek V4.1 Flash or Mixtral 8x7B?

DeepSeek V4.1 Flash is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Mixtral 8x7B lists at $0.70 and $0.70.

### Is DeepSeek V4.1 Flash or Mixtral 8x7B better for coding?

DeepSeek V4.1 Flash scores higher on coding benchmarks: 52.9 versus 32.8 in the Noometry coding category.

### Which has the bigger context window?

DeepSeek V4.1 Flash does, with 1M tokens against 32K.

### How many benchmarks do DeepSeek V4.1 Flash and Mixtral 8x7B share?

20 benchmarks have published results for both models. DeepSeek V4.1 Flash has 37 scored results on Noometry and Mixtral 8x7B has 38.