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. | 22B | 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 | May 29 2024 | Aug 18 2025 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
Codestral 22BvsClaude Haiku 5.5Nemotron Nano 2vsClaude Haiku 5.5Codestral 22BvsGPT-6.1 SolNemotron Nano 2vsGPT-6.1 SolCodestral 22BvsGemini 4 ArgonNemotron Nano 2vsGemini 4 ArgonCodestral 22BvsMuse Spark OpenNemotron Nano 2vsMuse Spark OpenCodestral 22BvsGrok 4.7Nemotron Nano 2vsGrok 4.7Codestral 22BvsDeepSeek-V4.1-Flash-1017Nemotron Nano 2vsDeepSeek-V4.1-Flash-1017Frequently asked questions
Codestral 22B and Nemotron Nano 2 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Codestral 22B shipped 446 days before Nemotron Nano 2, so benchmark comparisons should account for the intervening progress.
Codestral 22B has 22B parameters, while Nemotron Nano 2 has 9B. Context windows are 32k (Codestral 22B) vs 128k (Nemotron Nano 2). Codestral 22B is closed, while Nemotron Nano 2 is open weight.
Direct benchmark comparisons are unavailable — Codestral 22B and Nemotron Nano 2 don't publish scores on any of the same benchmarks.