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. | 236B | 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 | DeepSeek | NVIDIA |
| Release date | May 6 2024 | Oct 15 2024 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
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DeepSeek V2 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. DeepSeek V2 shipped 162 days before Llama 3.1 Nemotron 70B, so benchmark comparisons should account for the intervening progress.
DeepSeek V2 has 236B parameters, while Llama 3.1 Nemotron 70B has 70B. Context windows are 128k (DeepSeek V2) vs 128k (Llama 3.1 Nemotron 70B).
Direct benchmark comparisons are unavailable — DeepSeek V2 and Llama 3.1 Nemotron 70B don't publish scores on any of the same benchmarks.