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. | — | 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. | 256k | 128k |
| Overview | ||
| Company | Mistral | NVIDIA |
| Release date | Jan 13 2025 | Oct 15 2024 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
Codestral 25.01vsClaude Haiku 5.5Llama 3.1 Nemotron 70BvsClaude Haiku 5.5Codestral 25.01vsGPT-6.1 SolLlama 3.1 Nemotron 70BvsGPT-6.1 SolCodestral 25.01vsGemini 4 ArgonLlama 3.1 Nemotron 70BvsGemini 4 ArgonCodestral 25.01vsMuse Spark OpenLlama 3.1 Nemotron 70BvsMuse Spark OpenCodestral 25.01vsGrok 4.7Llama 3.1 Nemotron 70BvsGrok 4.7Codestral 25.01vsDeepSeek-V4.1-Flash-1017Llama 3.1 Nemotron 70BvsDeepSeek-V4.1-Flash-1017Frequently asked questions
Codestral 25.01 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. Llama 3.1 Nemotron 70B shipped 90 days before Codestral 25.01, so benchmark comparisons should account for the intervening progress.
Context windows are 256k (Codestral 25.01) vs 128k (Llama 3.1 Nemotron 70B). Codestral 25.01 is closed, while Llama 3.1 Nemotron 70B is open weight.
Direct benchmark comparisons are unavailable — Codestral 25.01 and Llama 3.1 Nemotron 70B don't publish scores on any of the same benchmarks.