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 | 8B/49B |
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 | Mar 18 2025 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
Ministral 3BvsClaude Haiku 5.5Llama Nemotron (Nano/Super)vsClaude Haiku 5.5Ministral 3BvsGPT-6.1 SolLlama Nemotron (Nano/Super)vsGPT-6.1 SolMinistral 3BvsGemini 4 ArgonLlama Nemotron (Nano/Super)vsGemini 4 ArgonMinistral 3BvsMuse Spark OpenLlama Nemotron (Nano/Super)vsMuse Spark OpenMinistral 3BvsGrok 4.7Llama Nemotron (Nano/Super)vsGrok 4.7Ministral 3BvsDeepSeek-V4.1-Flash-1017Llama Nemotron (Nano/Super)vsDeepSeek-V4.1-Flash-1017Frequently asked questions
Ministral 3B and Llama Nemotron (Nano/Super) don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Ministral 3B shipped 153 days before Llama Nemotron (Nano/Super), so benchmark comparisons should account for the intervening progress.
Ministral 3B has 3B parameters, while Llama Nemotron (Nano/Super) has 8B/49B. Context windows are 128k (Ministral 3B) vs 128k (Llama Nemotron (Nano/Super)).
Direct benchmark comparisons are unavailable — Ministral 3B and Llama Nemotron (Nano/Super) don't publish scores on any of the same benchmarks.