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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.
16B2B/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.
4k8k
Overview
CompanyDeepSeekGoogle
Release dateJan 11 2024Feb 21 2024
AccessOpen WeightOpen Weight
Model detailsView modelView model

Other comparisons

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Frequently asked questions

DeepSeek-MoE and Gemma 1 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. DeepSeek-MoE shipped 41 days before Gemma 1, so benchmark comparisons should account for the intervening progress.

DeepSeek-MoE has 16B parameters, while Gemma 1 has 2B/7B. Context windows are 4k (DeepSeek-MoE) vs 8k (Gemma 1).

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