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 | 9B |
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 | 128k |
| These models have no shared benchmark scores. | ||
BullshitBench v2Nonsense detection — Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. | — | 5% |
LiveCodeBenchCompetitive coding — Coding problems published so recently the AI can't have seen them in training — a contamination-free test of raw programming skill. Higher is better. | — | 71.1% |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | — | 64% |
| Overview | ||
| Company | Mistral | NVIDIA |
| Release date | Jul 16 2024 | Aug 18 2025 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
Mathstral 7BvsClaude Haiku 5.5Nemotron Nano 2vsClaude Haiku 5.5Mathstral 7BvsGPT-6.1 SolNemotron Nano 2vsGPT-6.1 SolMathstral 7BvsGemini 4 ArgonNemotron Nano 2vsGemini 4 ArgonMathstral 7BvsMuse Spark OpenNemotron Nano 2vsMuse Spark OpenMathstral 7BvsGrok 4.7Nemotron Nano 2vsGrok 4.7Mathstral 7BvsDeepSeek-V4.1-Flash-1017Nemotron Nano 2vsDeepSeek-V4.1-Flash-1017Frequently asked questions
Mathstral 7B and Nemotron Nano 2 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Mathstral 7B shipped 398 days before Nemotron Nano 2, so benchmark comparisons should account for the intervening progress.
Mathstral 7B has 7B parameters, while Nemotron Nano 2 has 9B. Context windows are 32k (Mathstral 7B) vs 128k (Nemotron Nano 2).
Direct benchmark comparisons are unavailable — Mathstral 7B and Nemotron Nano 2 don't publish scores on any of the same benchmarks.