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. | 7B | 340B |
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. | 32k | 4k |
| Overview | ||
| Company | Mistral | NVIDIA |
| Release date | Jul 16 2024 | Jun 14 2024 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
Mathstral 7BvsClaude Haiku 5.5Nemotron-4 340BvsClaude Haiku 5.5Mathstral 7BvsGPT-6.1 SolNemotron-4 340BvsGPT-6.1 SolMathstral 7BvsGemini 4 ArgonNemotron-4 340BvsGemini 4 ArgonMathstral 7BvsMuse Spark OpenNemotron-4 340BvsMuse Spark OpenMathstral 7BvsGrok 4.7Nemotron-4 340BvsGrok 4.7Mathstral 7BvsDeepSeek-V4.1-Flash-1017Nemotron-4 340BvsDeepSeek-V4.1-Flash-1017Frequently asked questions
Mathstral 7B and Nemotron-4 340B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Nemotron-4 340B shipped 32 days before Mathstral 7B, so benchmark comparisons should account for the intervening progress.
Mathstral 7B has 7B parameters, while Nemotron-4 340B has 340B. Context windows are 32k (Mathstral 7B) vs 4k (Nemotron-4 340B).
Direct benchmark comparisons are unavailable — Mathstral 7B and Nemotron-4 340B don't publish scores on any of the same benchmarks.