Model comparison
Llama 3.1-8B vs Mistral 7B
Llama 3.1-8B and Mistral 7B score almost the same on the Noometry Index (23.0 vs 23.0), so choose on price, context window or the category you care about most.
Last verified . 30 shared benchmarks.
Meta
Mistral AISummary
- They share 30 benchmarks with published results for both. Llama 3.1-8B scores higher in 6 categories and Mistral 7B in 2 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where Llama 3.1-8B leads 34.0 to 25.8.
- The biggest single-benchmark swing is MATH Level 5: 22.9% for Llama 3.1-8B and 3.7% for Mistral 7B.
- Llama 3.1-8B is cheaper at $0.05 / $0.08 per million input/output tokens, against $0.25 / $0.25 for Mistral 7B.
- Llama 3.1-8B accepts more context: 128K tokens versus 8K.
Side by side
| Llama 3.1-8B | Mistral 7B | |
|---|---|---|
| Provider | Meta | Mistral AI |
| Noometry Index | 23.0 | 23.0 |
| Released | 2024-07-23 | 2023-09-27 |
| Weights | Open | Open |
| Context window | 128K | 8K |
| Max output | 4K | 8K |
| Input $ / M tokens | $0.05 | $0.25 |
| Output $ / M tokens | $0.08 | $0.25 |
| Results tracked | 43 | 37 |
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Category by category
Coding Mistral 7B leads
Llama 3.1-8B: 20.2 (#340), Mistral 7B: 26.4 (#326)
| Benchmark | Llama 3.1-8B | Mistral 7B |
|---|---|---|
| BigCodeBench Instruct | 32.8% | 19.5% |
| LMArena Coding | 1195 | 1082 |
| BigCodeBench Complete | 40.5% | 27.3% |
| HumanEval+ | 62.8% | 36% |
| MBPP+ | 55.6% | 42.1% |
| SciCode | 13.2% | — |
| WeirdML | 1.7% | — |
Agentic & Tool Use Not comparable
Llama 3.1-8B: 22.5 (#131), Mistral 7B: —
| Benchmark | Llama 3.1-8B | Mistral 7B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 25.8% | — |
| BALROG | 15.1% | — |
Reasoning Llama 3.1-8B leads
Llama 3.1-8B: 14.9 (#321), Mistral 7B: 13.1 (#336)
| Benchmark | Llama 3.1-8B | Mistral 7B |
|---|---|---|
| Chess Puzzles | 0% | 0% |
| LMArena Hard Prompts | 1175 | 1067 |
| DTBench | 50.9% | 42.5% |
| Epoch Capabilities Index | 116.57 | 112.21 |
| PIQA | 81.2% | 83% |
| CritPt | 0% | — |
| LMCA | 5.4% | — |
| Adversarial NLI | — | 47.1% |
| BIG-Bench Hard | — | 56.1% |
| HellaSwag | — | 81% |
| WinoGrande | — | 75.3% |
Math Llama 3.1-8B leads
Llama 3.1-8B: 10.2 (#317), Mistral 7B: 8.1 (#325)
| Benchmark | Llama 3.1-8B | Mistral 7B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.7% | 0.3% |
| LMArena Math | 1179 | 1085 |
| MATH Level 5 | 22.9% | 3.7% |
| GSM8K | 82.4% | 54.4% |
| Omni-MATH | 13.7% | — |
Knowledge Too close to call
Llama 3.1-8B: 8.0 (#307), Mistral 7B: 7.4 (#311)
| Benchmark | Llama 3.1-8B | Mistral 7B |
|---|---|---|
| GPQA Diamond | 27% | 15.2% |
| LMArena Expert | 1144 | 1036 |
| BoolQ | 82.8% | 87.4% |
| MMLU | 56.1% | 62.5% |
| MMLU-Pro | 40.6% | — |
| GPQA (HELM) | 24.7% | — |
| ARC (AI2) Challenge | — | 78.6% |
| OpenBookQA | — | 79.8% |
| TriviaQA | — | 75.2% |
Multilingual Llama 3.1-8B leads
Llama 3.1-8B: 34.0 (#249), Mistral 7B: 25.8 (#283)
| Benchmark | Llama 3.1-8B | Mistral 7B |
|---|---|---|
| LMArena Non-English | 1148 | 1012 |
| LMArena Chinese | 1151 | 1009 |
| LMArena French | 1177 | 1037 |
| LMArena German | 1144 | 987 |
| LMArena Japanese | 1061 | 878 |
| LMArena Russian | 1158 | 1018 |
| LMArena Spanish | 1169 | 1026 |
| LMArena Korean | 1053 | — |
Instruction Following Llama 3.1-8B leads
Llama 3.1-8B: 58.9 (#258), Mistral 7B: 54.2 (#280)
| Benchmark | Llama 3.1-8B | Mistral 7B |
|---|---|---|
| LMArena Instruction Following | 1159 | 1060 |
| IFEval | 74.3% | — |
Long Context Llama 3.1-8B leads
Llama 3.1-8B: 35.8 (#238), Mistral 7B: 32.2 (#271)
| Benchmark | Llama 3.1-8B | Mistral 7B |
|---|---|---|
| LMArena Longer Query | 1182 | 1060 |
Writing & Preference Too close to call
Llama 3.1-8B: 29.7 (#290), Mistral 7B: 30.7 (#286)
| Benchmark | Llama 3.1-8B | Mistral 7B |
|---|---|---|
| LMArena Text | 1187 | 1090 |
| LMArena Creative Writing | 1154 | 1068 |
| LMArena Multi-Turn | 1172 | 1062 |
| EQ-Bench Creative Writing | 713 | — |
| WildBench | 68.7% | — |
Frequently asked questions
Is Llama 3.1-8B better than Mistral 7B?
Llama 3.1-8B and Mistral 7B score almost the same on the Noometry Index (23.0 vs 23.0), so choose on price, context window or the category you care about most.
Which is cheaper, Llama 3.1-8B or Mistral 7B?
Llama 3.1-8B is cheaper. It lists at $0.05 per million input tokens and $0.08 per million output tokens; Mistral 7B lists at $0.25 and $0.25.
Is Llama 3.1-8B or Mistral 7B better for coding?
Mistral 7B scores higher on coding benchmarks: 26.4 versus 20.2 in the Noometry coding category.
Which has the bigger context window?
Llama 3.1-8B does, with 128K tokens against 8K.
How many benchmarks do Llama 3.1-8B and Mistral 7B share?
30 benchmarks have published results for both models. Llama 3.1-8B has 43 scored results on Noometry and Mistral 7B has 37.