# Llama 3.1-8B vs Mixtral 8x22B

> Mixtral 8x22B is the stronger model overall, scoring 26.7 to 22.8 on the Noometry Index. Llama 3.1-8B costs 52× less per token, which makes it the better buy when Mixtral 8x22B's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/llama-3-1-8b-vs-mixtral-8x22b
- Last updated: 2026-10-10
- Shared benchmarks: 32

## Summary

- They share 32 benchmarks with published results for both. Llama 3.1-8B scores higher in 3 categories and Mixtral 8x22B in 6 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Mixtral 8x22B leads 21.2 to 9.5.
- The biggest single-benchmark swing is BigCodeBench Complete: 40.5% for Llama 3.1-8B and 50.2% for Mixtral 8x22B.
- Llama 3.1-8B is cheaper at $0.05 / $0.08 per million input/output tokens, against $2 / $6 for Mixtral 8x22B.
- Llama 3.1-8B accepts more context: 128K tokens versus 64K.

## Snapshot

| | Llama 3.1-8B | Mixtral 8x22B |
|---|---|---|
| Provider | Meta | Mistral AI |
| Noometry Index | 22.8 | 26.7 |
| Rank | 347 | 330 |
| Context | 128K | 64K |
| Input $/M | $0.05 | $2 |
| Output $/M | $0.08 | $6 |
| Weights | Open | Open |

## Coding

- Llama 3.1-8B: 19.9 (#335)
- Mixtral 8x22B: 23.8 (#324)

| Benchmark | Llama 3.1-8B | Mixtral 8x22B |
|---|---|---|
| WeirdML | 1.7% | 3.2% |
| BigCodeBench Instruct | 32.8% | 40.6% |
| LMArena Coding | 1195 | 1166 |
| BigCodeBench Complete | 40.5% | 50.2% |
| HumanEval+ | 62.8% | 72% |
| MBPP+ | 55.6% | 64.3% |
| SciCode | 13.2% | — |

## Agentic & Tool Use

- Llama 3.1-8B: 22.3 (#123)
- Mixtral 8x22B: 22.8 (#119)

| Benchmark | Llama 3.1-8B | Mixtral 8x22B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 25.8% | — |
| Cybench | — | 7.5% |
| BALROG | 15.1% | — |

## Reasoning

- Llama 3.1-8B: 14.5 (#316)
- Mixtral 8x22B: 19.1 (#246)

| Benchmark | Llama 3.1-8B | Mixtral 8x22B |
|---|---|---|
| LMArena Hard Prompts | 1175 | 1150 |
| DTBench | 50.9% | 55.1% |
| Epoch Capabilities Index | 116.48 | 122 |
| CritPt | 0% | — |
| Chess Puzzles | 0% | — |
| LMCA | 5.4% | — |
| ForecastBench | — | 56.3 |
| PIQA | 81.2% | — |

## Math

- Llama 3.1-8B: 9.5 (#311)
- Mixtral 8x22B: 21.2 (#271)

| Benchmark | Llama 3.1-8B | Mixtral 8x22B |
|---|---|---|
| Omni-MATH | 13.7% | 16.3% |
| LMArena Math | 1179 | 1184 |
| MATH Level 5 | 22.9% | 24.2% |
| OTIS Mock AIME 2024-2025 | 1.7% | — |
| GSM8K | 82.4% | — |

## Knowledge

- Llama 3.1-8B: 8.0 (#302)
- Mixtral 8x22B: 15.1 (#288)

| Benchmark | Llama 3.1-8B | Mixtral 8x22B |
|---|---|---|
| GPQA Diamond | 27% | 34.1% |
| MMLU-Pro | 40.6% | 46% |
| GPQA (HELM) | 24.7% | 33.4% |
| LMArena Expert | 1144 | 1113 |
| MMLU | 56.1% | 77.8% |
| BoolQ | 82.8% | — |

## Multilingual

- Llama 3.1-8B: 34.2 (#244)
- Mixtral 8x22B: 32.9 (#250)

| Benchmark | Llama 3.1-8B | Mixtral 8x22B |
|---|---|---|
| LMArena Non-English | 1148 | 1128 |
| LMArena Chinese | 1151 | 1116 |
| LMArena French | 1176 | 1165 |
| LMArena German | 1144 | 1141 |
| LMArena Japanese | 1061 | 1037 |
| LMArena Korean | 1053 | 1056 |
| LMArena Russian | 1158 | 1158 |
| LMArena Spanish | 1169 | 1150 |

## Instruction Following

- Llama 3.1-8B: 59.1 (#253)
- Mixtral 8x22B: 57.9 (#261)

| Benchmark | Llama 3.1-8B | Mixtral 8x22B |
|---|---|---|
| IFEval | 74.3% | 72.4% |
| LMArena Instruction Following | 1159 | 1147 |

## Long Context

- Llama 3.1-8B: 35.8 (#233)
- Mixtral 8x22B: 34.6 (#242)

| Benchmark | Llama 3.1-8B | Mixtral 8x22B |
|---|---|---|
| LMArena Longer Query | 1182 | 1144 |

## Writing & Preference

- Llama 3.1-8B: 29.9 (#285)
- Mixtral 8x22B: 37.1 (#257)

| Benchmark | Llama 3.1-8B | Mixtral 8x22B |
|---|---|---|
| LMArena Text | 1187 | 1162 |
| LMArena Creative Writing | 1154 | 1141 |
| WildBench | 68.7% | 71.1% |
| LMArena Multi-Turn | 1172 | 1130 |
| EQ-Bench Creative Writing | 713 | — |

## FAQ

### Is Llama 3.1-8B better than Mixtral 8x22B?

Mixtral 8x22B is the stronger model overall, scoring 26.7 to 22.8 on the Noometry Index. Llama 3.1-8B costs 52× less per token, which makes it the better buy when Mixtral 8x22B's lead doesn't matter for your workload.

### Which is cheaper, Llama 3.1-8B or Mixtral 8x22B?

Llama 3.1-8B is cheaper. It lists at $0.05 per million input tokens and $0.08 per million output tokens; Mixtral 8x22B lists at $2 and $6.

### Is Llama 3.1-8B or Mixtral 8x22B better for coding?

Mixtral 8x22B scores higher on coding benchmarks: 23.8 versus 19.9 in the Noometry coding category.

### Which has the bigger context window?

Llama 3.1-8B does, with 128K tokens against 64K.

### How many benchmarks do Llama 3.1-8B and Mixtral 8x22B share?

32 benchmarks have published results for both models. Llama 3.1-8B has 43 scored results on Noometry and Mixtral 8x22B has 34.