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. | — | 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. | 2M | 128k |
| Overview | ||
| Company | NVIDIA | |
| Release date | Sep 24 2024 | Oct 15 2024 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
Gemini 1.5 Pro-002vsClaude Haiku 5.5Llama 3.1 Nemotron 70BvsClaude Haiku 5.5Gemini 1.5 Pro-002vsGPT-6.1 SolLlama 3.1 Nemotron 70BvsGPT-6.1 SolGemini 1.5 Pro-002vsMuse Spark OpenLlama 3.1 Nemotron 70BvsMuse Spark OpenGemini 1.5 Pro-002vsGrok 4.7Llama 3.1 Nemotron 70BvsGrok 4.7Gemini 1.5 Pro-002vsDeepSeek-V4.1-Flash-1017Llama 3.1 Nemotron 70BvsDeepSeek-V4.1-Flash-1017Gemini 1.5 Pro-002vsMistral Large 4Llama 3.1 Nemotron 70BvsMistral Large 4Frequently asked questions
Gemini 1.5 Pro-002 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. Gemini 1.5 Pro-002 shipped 21 days before Llama 3.1 Nemotron 70B, so benchmark comparisons should account for the intervening progress.
Context windows are 2M (Gemini 1.5 Pro-002) vs 128k (Llama 3.1 Nemotron 70B). Gemini 1.5 Pro-002 is closed, while Llama 3.1 Nemotron 70B is open weight.
Direct benchmark comparisons are unavailable — Gemini 1.5 Pro-002 and Llama 3.1 Nemotron 70B don't publish scores on any of the same benchmarks.