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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.
236B2B/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.
128k8k
Overview
CompanyDeepSeekGoogle
Release dateMay 6 2024Feb 21 2024
AccessOpen WeightOpen Weight
Model detailsView modelView model

Other comparisons

DeepSeek V2vsClaude Haiku 5.5Gemma 1vsClaude Haiku 5.5DeepSeek V2vsGPT-6.1 SolGemma 1vsGPT-6.1 SolDeepSeek V2vsMuse Spark OpenGemma 1vsMuse Spark OpenDeepSeek V2vsGrok 4.7Gemma 1vsGrok 4.7DeepSeek V2vsMistral Large 4Gemma 1vsMistral Large 4DeepSeek V2vsKimi K3Gemma 1vsKimi K3

Frequently asked questions

DeepSeek V2 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 75 days before DeepSeek V2, so benchmark comparisons should account for the intervening progress.

DeepSeek V2 has 236B parameters, while Gemma 1 has 2B/7B. Context windows are 128k (DeepSeek V2) vs 8k (Gemma 1).

Direct benchmark comparisons are unavailable — DeepSeek V2 and Gemma 1 don't publish scores on any of the same benchmarks.