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. | 2B/7B | 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. | 8k | 128k |
| Overview | ||
| Company | NVIDIA | |
| Release date | Feb 21 2024 | Mar 18 2025 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
Gemma 1vsClaude Haiku 5.5Llama Nemotron (Nano/Super)vsClaude Haiku 5.5Gemma 1vsGPT-6.1 SolLlama Nemotron (Nano/Super)vsGPT-6.1 SolGemma 1vsMuse Spark OpenLlama Nemotron (Nano/Super)vsMuse Spark OpenGemma 1vsGrok 4.7Llama Nemotron (Nano/Super)vsGrok 4.7Gemma 1vsDeepSeek-V4.1-Flash-1017Llama Nemotron (Nano/Super)vsDeepSeek-V4.1-Flash-1017Gemma 1vsMistral Large 4Llama Nemotron (Nano/Super)vsMistral Large 4Frequently asked questions
Gemma 1 and Llama Nemotron (Nano/Super) don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Gemma 1 shipped 391 days before Llama Nemotron (Nano/Super), so benchmark comparisons should account for the intervening progress.
Gemma 1 has 2B/7B parameters, while Llama Nemotron (Nano/Super) has 8B/49B. Context windows are 8k (Gemma 1) vs 128k (Llama Nemotron (Nano/Super)).
Direct benchmark comparisons are unavailable — Gemma 1 and Llama Nemotron (Nano/Super) don't publish scores on any of the same benchmarks.