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 | 340B |
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 | 4k |
| Overview | ||
| Company | DeepSeek | NVIDIA |
| Release date | Dec 10 2024 | Jun 14 2024 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
DeepSeek V2.5 (Revised)vsClaude Haiku 5.5Nemotron-4 340BvsClaude Haiku 5.5DeepSeek V2.5 (Revised)vsGPT-6.1 SolNemotron-4 340BvsGPT-6.1 SolDeepSeek V2.5 (Revised)vsGemini 4 ArgonNemotron-4 340BvsGemini 4 ArgonDeepSeek V2.5 (Revised)vsMuse Spark OpenNemotron-4 340BvsMuse Spark OpenDeepSeek V2.5 (Revised)vsGrok 4.7Nemotron-4 340BvsGrok 4.7DeepSeek V2.5 (Revised)vsMistral Large 4Nemotron-4 340BvsMistral Large 4Frequently asked questions
DeepSeek V2.5 (Revised) and Nemotron-4 340B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Nemotron-4 340B shipped 179 days before DeepSeek V2.5 (Revised), so benchmark comparisons should account for the intervening progress.
DeepSeek V2.5 (Revised) has 236B parameters, while Nemotron-4 340B has 340B. Context windows are 128k (DeepSeek V2.5 (Revised)) vs 4k (Nemotron-4 340B).
Direct benchmark comparisons are unavailable — DeepSeek V2.5 (Revised) and Nemotron-4 340B don't publish scores on any of the same benchmarks.