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 | 8B |
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 | 1M |
| Overview | ||
| Company | DeepSeek | |
| Release date | May 6 2024 | Oct 3 2024 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
DeepSeek V2vsClaude Haiku 5.5Gemini 1.5 Flash-8BvsClaude Haiku 5.5DeepSeek V2vsGPT-6.1 SolGemini 1.5 Flash-8BvsGPT-6.1 SolDeepSeek V2vsMuse Spark OpenGemini 1.5 Flash-8BvsMuse Spark OpenDeepSeek V2vsGrok 4.7Gemini 1.5 Flash-8BvsGrok 4.7DeepSeek V2vsMistral Large 4Gemini 1.5 Flash-8BvsMistral Large 4DeepSeek V2vsKimi K3Gemini 1.5 Flash-8BvsKimi K3Frequently asked questions
DeepSeek V2 and Gemini 1.5 Flash-8B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. DeepSeek V2 shipped 150 days before Gemini 1.5 Flash-8B, so benchmark comparisons should account for the intervening progress.
DeepSeek V2 has 236B parameters, while Gemini 1.5 Flash-8B has 8B. Context windows are 128k (DeepSeek V2) vs 1M (Gemini 1.5 Flash-8B). DeepSeek V2 is open weight, while Gemini 1.5 Flash-8B is closed.
Direct benchmark comparisons are unavailable — DeepSeek V2 and Gemini 1.5 Flash-8B don't publish scores on any of the same benchmarks.