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 | 2B/7B |
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 | 8k |
| Overview | ||
| Company | DeepSeek | |
| Release date | Dec 10 2024 | Feb 21 2024 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
DeepSeek V2.5 (Revised)vsClaude Haiku 5.5Gemma 1vsClaude Haiku 5.5DeepSeek V2.5 (Revised)vsGPT-6.1 SolGemma 1vsGPT-6.1 SolDeepSeek V2.5 (Revised)vsMuse Spark OpenGemma 1vsMuse Spark OpenDeepSeek V2.5 (Revised)vsGrok 4.7Gemma 1vsGrok 4.7DeepSeek V2.5 (Revised)vsMistral Large 4Gemma 1vsMistral Large 4DeepSeek V2.5 (Revised)vsKimi K3Gemma 1vsKimi K3Frequently asked questions
DeepSeek V2.5 (Revised) and Gemma 1 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Gemma 1 shipped 293 days before DeepSeek V2.5 (Revised), so benchmark comparisons should account for the intervening progress.
DeepSeek V2.5 (Revised) has 236B parameters, while Gemma 1 has 2B/7B. Context windows are 128k (DeepSeek V2.5 (Revised)) vs 8k (Gemma 1).
Direct benchmark comparisons are unavailable — DeepSeek V2.5 (Revised) and Gemma 1 don't publish scores on any of the same benchmarks.