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. | 3B | 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 | Oct 16 2024 | Oct 15 2024 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
Ministral 3BvsClaude Haiku 5.5Llama 3.1 Nemotron 70BvsClaude Haiku 5.5Ministral 3BvsGPT-6.1 SolLlama 3.1 Nemotron 70BvsGPT-6.1 SolMinistral 3BvsGemini 4 ArgonLlama 3.1 Nemotron 70BvsGemini 4 ArgonMinistral 3BvsMuse Spark OpenLlama 3.1 Nemotron 70BvsMuse Spark OpenMinistral 3BvsGrok 4.7Llama 3.1 Nemotron 70BvsGrok 4.7Ministral 3BvsDeepSeek-V4.1-Flash-1017Llama 3.1 Nemotron 70BvsDeepSeek-V4.1-Flash-1017Frequently asked questions
Ministral 3B 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 1 days before Ministral 3B, so benchmark comparisons should account for the intervening progress.
Ministral 3B has 3B parameters, while Llama 3.1 Nemotron 70B has 70B. Context windows are 128k (Ministral 3B) vs 128k (Llama 3.1 Nemotron 70B).
Direct benchmark comparisons are unavailable — Ministral 3B and Llama 3.1 Nemotron 70B don't publish scores on any of the same benchmarks.