Model comparison
Llama 3.1-405B vs Pixtral Large
Pixtral Large is the stronger model overall, scoring 31.7 to 30.4 on the Noometry Index.
Last verified . 1 shared benchmarks.
Meta
Mistral AISummary
- They share 1 benchmark with published results for both. Llama 3.1-405B scores higher in 1 category and Pixtral Large in 1 category; 2 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Llama 3.1-405B leads 39.1 to 32.9.
Side by side
| Llama 3.1-405B | Pixtral Large | |
|---|---|---|
| Provider | Meta | Mistral AI |
| Noometry Index | 30.4 | 31.7 |
| Released | 2024-07-23 | 2024-11-01 |
| Weights | Open | Open |
| Context window | — | 128K |
| Max output | — | 128K |
| Input $ / M tokens | — | $2 |
| Output $ / M tokens | — | $6 |
| Results tracked | 42 | 3 |
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Category by category
Coding Not comparable
Llama 3.1-405B: 32.7 (#257), Pixtral Large: —
| Benchmark | Llama 3.1-405B | Pixtral Large |
|---|---|---|
| WeirdML | 21.4% | — |
| LMArena Coding | 1291 | — |
Agentic & Tool Use Not comparable
Llama 3.1-405B: 20.9 (#131), Pixtral Large: —
| Benchmark | Llama 3.1-405B | Pixtral Large |
|---|---|---|
| TheAgentCompany | 7.4% | — |
| Cybench | 7.5% | — |
Reasoning Pixtral Large leads
Llama 3.1-405B: 16.4 (#293), Pixtral Large: 20.9 (#208)
| Benchmark | Llama 3.1-405B | Pixtral Large |
|---|---|---|
| SimpleBench | 23% | — |
| Kagi LLM Benchmark | 45% | — |
| EnigmaEval | — | 0.8% |
| LMArena Hard Prompts | 1270 | — |
| DTBench | 61.4% | — |
| BIG-Bench Hard | 82.9% | — |
| Epoch Capabilities Index | 128.76 | — |
| ForecastBench | 59.9 | — |
| HellaSwag | 89.2% | — |
| PIQA | 85.9% | — |
| WinoGrande | 89.2% | — |
Math Not comparable
Llama 3.1-405B: 17.3 (#283), Pixtral Large: —
| Benchmark | Llama 3.1-405B | Pixtral Large |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 9.7% | — |
| Omni-MATH | 24.9% | — |
| LMArena Math | 1281 | — |
| MATH Level 5 | 49.8% | — |
Knowledge Not comparable
Llama 3.1-405B: 30.4 (#221), Pixtral Large: —
| Benchmark | Llama 3.1-405B | Pixtral Large |
|---|---|---|
| GPQA Diamond | 50.9% | — |
| MMLU-Pro | 72.3% | — |
| Confabulations | 17.6% | — |
| GPQA (HELM) | 52.2% | — |
| LMArena Expert | 1243 | — |
| ARC (AI2) Challenge | 95.3% | — |
| MMLU | 84.5% | — |
| TriviaQA | 82.7% | — |
Multimodal Not comparable
Llama 3.1-405B: —, Pixtral Large: 30.0 (#105)
| Benchmark | Llama 3.1-405B | Pixtral Large |
|---|---|---|
| LMArena Vision | — | 1089 |
Multilingual Not comparable
Llama 3.1-405B: 40.9 (#209), Pixtral Large: —
| Benchmark | Llama 3.1-405B | Pixtral Large |
|---|---|---|
| LMArena Non-English | 1248 | — |
| LMArena Chinese | 1242 | — |
| LMArena French | 1278 | — |
| LMArena German | 1252 | — |
| LMArena Japanese | 1208 | — |
| LMArena Korean | 1184 | — |
| LMArena Russian | 1265 | — |
| LMArena Spanish | 1259 | — |
Instruction Following Not comparable
Llama 3.1-405B: 66.1 (#209), Pixtral Large: —
| Benchmark | Llama 3.1-405B | Pixtral Large |
|---|---|---|
| IFEval | 81.1% | — |
| LMArena Instruction Following | 1259 | — |
Long Context Not comparable
Llama 3.1-405B: 38.4 (#192), Pixtral Large: —
| Benchmark | Llama 3.1-405B | Pixtral Large |
|---|---|---|
| LMArena Longer Query | 1266 | — |
Writing & Preference Llama 3.1-405B leads
Llama 3.1-405B: 39.1 (#246), Pixtral Large: 32.9 (#273)
| Benchmark | Llama 3.1-405B | Pixtral Large |
|---|---|---|
| EQ-Bench Creative Writing | 870 | 988 |
| LMArena Text | 1284 | — |
| LMArena Creative Writing | 1262 | — |
| WildBench | 78.3% | — |
| LMArena Multi-Turn | 1297 | — |
Frequently asked questions
Is Llama 3.1-405B better than Pixtral Large?
Pixtral Large is the stronger model overall, scoring 31.7 to 30.4 on the Noometry Index.
How many benchmarks do Llama 3.1-405B and Pixtral Large share?
1 benchmark has published results for both models. Llama 3.1-405B has 42 scored results on Noometry and Pixtral Large has 3.