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/13B/70B | 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. | 4k | 128k |
| Overview | ||
| Company | Meta | NVIDIA |
| Release date | Jul 18 2023 | Oct 15 2024 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
LLaMA 2vsClaude Haiku 5.5Llama 3.1 Nemotron 70BvsClaude Haiku 5.5LLaMA 2vsGPT-6.1 SolLlama 3.1 Nemotron 70BvsGPT-6.1 SolLLaMA 2vsGemini 4 ArgonLlama 3.1 Nemotron 70BvsGemini 4 ArgonLLaMA 2vsGrok 4.7Llama 3.1 Nemotron 70BvsGrok 4.7LLaMA 2vsDeepSeek-V4.1-Flash-1017Llama 3.1 Nemotron 70BvsDeepSeek-V4.1-Flash-1017LLaMA 2vsMistral Large 4Llama 3.1 Nemotron 70BvsMistral Large 4Frequently asked questions
LLaMA 2 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 2 shipped 455 days before Llama 3.1 Nemotron 70B, so benchmark comparisons should account for the intervening progress.
LLaMA 2 has 7B/13B/70B parameters, while Llama 3.1 Nemotron 70B has 70B. Context windows are 4k (LLaMA 2) vs 128k (Llama 3.1 Nemotron 70B).
Direct benchmark comparisons are unavailable — LLaMA 2 and Llama 3.1 Nemotron 70B don't publish scores on any of the same benchmarks.