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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.
236B7B/13B/33B/65B
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.
128k2k
Overview
CompanyDeepSeekMeta
Release dateMay 6 2024Feb 24 2023
AccessOpen WeightOpen Weight
Model detailsView modelView model

Other comparisons

DeepSeek V2vsClaude Haiku 5.5LLaMA 1vsClaude Haiku 5.5DeepSeek V2vsGPT-6.1 SolLLaMA 1vsGPT-6.1 SolDeepSeek V2vsGemini 4 ArgonLLaMA 1vsGemini 4 ArgonDeepSeek V2vsGrok 4.7LLaMA 1vsGrok 4.7DeepSeek V2vsMistral Large 4LLaMA 1vsMistral Large 4DeepSeek V2vsKimi K3LLaMA 1vsKimi K3

Frequently asked questions

DeepSeek V2 and LLaMA 1 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. LLaMA 1 shipped 437 days before DeepSeek V2, so benchmark comparisons should account for the intervening progress.

DeepSeek V2 has 236B parameters, while LLaMA 1 has 7B/13B/33B/65B. Context windows are 128k (DeepSeek V2) vs 2k (LLaMA 1).

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