# Llama 3.1-8B vs Mistral

> Mistral is the stronger model overall, scoring 29.9 to 23.0 on the Noometry Index.

- Canonical page: https://noometry.com/compare/llama-3-1-8b-vs-mistral
- Last updated: 2026-10-10
- Shared benchmarks: 22

## Summary

- They share 22 benchmarks with published results for both. Llama 3.1-8B scores higher in 3 categories and Mistral in 5 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in coding, where Mistral leads 33.8 to 20.2.
- The biggest single-benchmark swing is IFEval: 74.3% for Llama 3.1-8B and 56.8% for Mistral.
- Llama 3.1-8B has downloadable open weights; the other is API-only.

## Snapshot

| | Llama 3.1-8B | Mistral |
|---|---|---|
| Provider | Meta | Mistral AI |
| Noometry Index | 23.0 | 29.9 |
| Rank | 352 | 303 |
| Context | 128K | — |
| Input $/M | $0.05 | — |
| Output $/M | $0.08 | — |
| Weights | Open | Proprietary |

## Coding

- Llama 3.1-8B: 20.2 (#340)
- Mistral: 33.8 (#250)

| Benchmark | Llama 3.1-8B | Mistral |
|---|---|---|
| LMArena Coding | 1195 | 1162 |
| SciCode | 13.2% | — |
| WeirdML | 1.7% | — |
| BigCodeBench Instruct | 32.8% | — |
| BigCodeBench Complete | 40.5% | — |
| HumanEval+ | 62.8% | — |
| MBPP+ | 55.6% | — |

## Agentic & Tool Use

- Llama 3.1-8B: 22.5 (#131)
- Mistral: —

| Benchmark | Llama 3.1-8B | Mistral |
|---|---|---|
| Berkeley Function Calling Leaderboard | 25.8% | — |
| BALROG | 15.1% | — |

## Reasoning

- Llama 3.1-8B: 14.9 (#321)
- Mistral: 22.2 (#200)

| Benchmark | Llama 3.1-8B | Mistral |
|---|---|---|
| LMArena Hard Prompts | 1175 | 1149 |
| CritPt | 0% | — |
| Chess Puzzles | 0% | — |
| DTBench | 50.9% | — |
| LMCA | 5.4% | — |
| Epoch Capabilities Index | 116.57 | — |
| PIQA | 81.2% | — |

## Math

- Llama 3.1-8B: 10.2 (#317)
- Mistral: 22.3 (#278)

| Benchmark | Llama 3.1-8B | Mistral |
|---|---|---|
| Omni-MATH | 13.7% | 7.2% |
| LMArena Math | 1179 | 1180 |
| OTIS Mock AIME 2024-2025 | 1.7% | — |
| MATH Level 5 | 22.9% | — |
| GSM8K | 82.4% | — |

## Knowledge

- Llama 3.1-8B: 8.0 (#307)
- Mistral: 16.6 (#288)

| Benchmark | Llama 3.1-8B | Mistral |
|---|---|---|
| MMLU-Pro | 40.6% | 27.7% |
| GPQA (HELM) | 24.7% | 30.3% |
| LMArena Expert | 1144 | 1125 |
| GPQA Diamond | 27% | — |
| BoolQ | 82.8% | — |
| MMLU | 56.1% | — |

## Multilingual

- Llama 3.1-8B: 34.0 (#249)
- Mistral: 32.8 (#254)

| Benchmark | Llama 3.1-8B | Mistral |
|---|---|---|
| LMArena Non-English | 1148 | 1129 |
| LMArena Chinese | 1151 | 1109 |
| LMArena French | 1177 | 1180 |
| LMArena German | 1144 | 1155 |
| LMArena Japanese | 1061 | 1013 |
| LMArena Korean | 1053 | 1032 |
| LMArena Russian | 1158 | 1168 |
| LMArena Spanish | 1169 | 1143 |

## Instruction Following

- Llama 3.1-8B: 58.9 (#258)
- Mistral: 52.6 (#288)

| Benchmark | Llama 3.1-8B | Mistral |
|---|---|---|
| IFEval | 74.3% | 56.8% |
| LMArena Instruction Following | 1159 | 1152 |

## Long Context

- Llama 3.1-8B: 35.8 (#238)
- Mistral: 35.0 (#245)

| Benchmark | Llama 3.1-8B | Mistral |
|---|---|---|
| LMArena Longer Query | 1182 | 1153 |

## Writing & Preference

- Llama 3.1-8B: 29.7 (#290)
- Mistral: 37.0 (#260)

| Benchmark | Llama 3.1-8B | Mistral |
|---|---|---|
| LMArena Text | 1187 | 1165 |
| LMArena Creative Writing | 1154 | 1158 |
| WildBench | 68.7% | 66% |
| LMArena Multi-Turn | 1172 | 1147 |
| EQ-Bench Creative Writing | 713 | — |

## FAQ

### Is Llama 3.1-8B better than Mistral?

Mistral is the stronger model overall, scoring 29.9 to 23.0 on the Noometry Index.

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

Mistral scores higher on coding benchmarks: 33.8 versus 20.2 in the Noometry coding category.

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

22 benchmarks have published results for both models. Llama 3.1-8B has 43 scored results on Noometry and Mistral has 22.