Model comparison
Llama 3.1-70B vs Pixtral Large
Pixtral Large is the stronger model overall, scoring 32.2 to 29.6 on the Noometry Index. Llama 3.1-70B costs 7.5× less per token, which makes it the better buy when Pixtral Large's lead doesn't matter for your workload.
Last verified . 1 shared benchmarks.
Meta
Mistral AISummary
- They share 1 benchmark with published results for both. Llama 3.1-70B scores higher in 1 category and Pixtral Large in 1 category; one gap is clear of the uncertainty.
- Llama 3.1-70B is cheaper at $0.40 / $0.40 per million input/output tokens, against $2 / $6 for Pixtral Large.
Side by side
| Llama 3.1-70B | Pixtral Large | |
|---|---|---|
| Provider | Meta | Mistral AI |
| Noometry Index | 29.6 | 32.2 |
| Released | 2024-07-23 | 2024-11-01 |
| Weights | Open | Open |
| Context window | 128K | 128K |
| Max output | 4K | 128K |
| Input $ / M tokens | $0.40 | $2 |
| Output $ / M tokens | $0.40 | $6 |
| Results tracked | 35 | 3 |
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Category by category
Coding Not comparable
Llama 3.1-70B: 30.3 (#296), Pixtral Large: —
| Benchmark | Llama 3.1-70B | Pixtral Large |
|---|---|---|
| WeirdML | 9% | — |
| BigCodeBench Instruct | 46.1% | — |
| LMArena Coding | 1260 | — |
| BigCodeBench Complete | 54.8% | — |
Agentic & Tool Use Not comparable
Llama 3.1-70B: 25.1 (#112), Pixtral Large: —
| Benchmark | Llama 3.1-70B | Pixtral Large |
|---|---|---|
| TheAgentCompany | 6.9% | — |
| BALROG | 27.9% | — |
Reasoning Too close to call
Llama 3.1-70B: 21.6 (#220), Pixtral Large: 21.7 (#218)
| Benchmark | Llama 3.1-70B | Pixtral Large |
|---|---|---|
| EnigmaEval | — | 0.8% |
| LMArena Hard Prompts | 1241 | — |
| DTBench | 60% | — |
| LMCA | 14.8% | — |
| Epoch Capabilities Index | 125.92 | — |
Math Not comparable
Llama 3.1-70B: 13.5 (#304), Pixtral Large: —
| Benchmark | Llama 3.1-70B | Pixtral Large |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 3.6% | — |
| Omni-MATH | 21% | — |
| LMArena Math | 1252 | — |
| MATH Level 5 | 36.7% | — |
Knowledge Not comparable
Llama 3.1-70B: 24.2 (#269), Pixtral Large: —
| Benchmark | Llama 3.1-70B | Pixtral Large |
|---|---|---|
| GPQA Diamond | 44.2% | — |
| MMLU-Pro | 65.3% | — |
| GPQA (HELM) | 42.6% | — |
| LMArena Expert | 1209 | — |
| MMLU | 80.1% | — |
Multimodal Not comparable
Llama 3.1-70B: —, Pixtral Large: 30.6 (#111)
| Benchmark | Llama 3.1-70B | Pixtral Large |
|---|---|---|
| LMArena Vision | — | 1089 |
Multilingual Not comparable
Llama 3.1-70B: 38.8 (#225), Pixtral Large: —
| Benchmark | Llama 3.1-70B | Pixtral Large |
|---|---|---|
| LMArena Non-English | 1219 | — |
| LMArena Chinese | 1215 | — |
| LMArena French | 1261 | — |
| LMArena German | 1222 | — |
| LMArena Japanese | 1132 | — |
| LMArena Korean | 1140 | — |
| LMArena Russian | 1234 | — |
| LMArena Spanish | 1253 | — |
Instruction Following Not comparable
Llama 3.1-70B: 65.3 (#223), Pixtral Large: —
| Benchmark | Llama 3.1-70B | Pixtral Large |
|---|---|---|
| IFEval | 82.1% | — |
| LMArena Instruction Following | 1231 | — |
Long Context Not comparable
Llama 3.1-70B: 37.6 (#214), Pixtral Large: —
| Benchmark | Llama 3.1-70B | Pixtral Large |
|---|---|---|
| LMArena Longer Query | 1241 | — |
Writing & Preference Llama 3.1-70B leads
Llama 3.1-70B: 35.4 (#267), Pixtral Large: 32.9 (#278)
| Benchmark | Llama 3.1-70B | Pixtral Large |
|---|---|---|
| EQ-Bench Creative Writing | 784 | 988 |
| LMArena Text | 1261 | — |
| LMArena Creative Writing | 1232 | — |
| WildBench | 75.8% | — |
| LMArena Multi-Turn | 1256 | — |
Frequently asked questions
Is Llama 3.1-70B better than Pixtral Large?
Pixtral Large is the stronger model overall, scoring 32.2 to 29.6 on the Noometry Index. Llama 3.1-70B costs 7.5× less per token, which makes it the better buy when Pixtral Large's lead doesn't matter for your workload.
Which is cheaper, Llama 3.1-70B or Pixtral Large?
Llama 3.1-70B is cheaper. It lists at $0.40 per million input tokens and $0.40 per million output tokens; Pixtral Large lists at $2 and $6.
Which has the bigger context window?
Both accept 128K tokens.
How many benchmarks do Llama 3.1-70B and Pixtral Large share?
1 benchmark has published results for both models. Llama 3.1-70B has 35 scored results on Noometry and Pixtral Large has 3.