Compare AI models
| Specifications | ||
ParametersThe learned values that shape how a model responds. B means billion and T means trillion. For mixture-of-experts models, the total count is larger than the number active for each token. Parameter count alone does not measure quality. | 12B | 70B |
Context windowHow much information the model can work with in one request, measured in tokens — pieces of words or other data. This includes your question, attachments, conversation and reply. Limits can vary by model variant and provider. | 128k | 128k |
| Overview | ||
| Company | Mistral | NVIDIA |
| Release date | Sep 11 2024 | Oct 15 2024 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
Pixtral 24.09vsClaude Haiku 5.5Llama 3.1 Nemotron 70BvsClaude Haiku 5.5Pixtral 24.09vsGPT-6.1 SolLlama 3.1 Nemotron 70BvsGPT-6.1 SolPixtral 24.09vsGemini 4 ArgonLlama 3.1 Nemotron 70BvsGemini 4 ArgonPixtral 24.09vsMuse Spark OpenLlama 3.1 Nemotron 70BvsMuse Spark OpenPixtral 24.09vsGrok 4.7Llama 3.1 Nemotron 70BvsGrok 4.7Pixtral 24.09vsDeepSeek-V4.1-Flash-1017Llama 3.1 Nemotron 70BvsDeepSeek-V4.1-Flash-1017Frequently asked questions
Pixtral 24.09 and Llama 3.1 Nemotron 70B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Pixtral 24.09 shipped 34 days before Llama 3.1 Nemotron 70B, so benchmark comparisons should account for the intervening progress.
Pixtral 24.09 has 12B parameters, while Llama 3.1 Nemotron 70B has 70B. Context windows are 128k (Pixtral 24.09) vs 128k (Llama 3.1 Nemotron 70B).
Direct benchmark comparisons are unavailable — Pixtral 24.09 and Llama 3.1 Nemotron 70B don't publish scores on any of the same benchmarks.