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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.
2B/7B7B/13B/70B
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.
8k4k
Overview
CompanyGoogleMeta
Release dateFeb 21 2024Jul 18 2023
AccessOpen WeightOpen Weight
Model detailsView modelView model

Other comparisons

Gemma 1vsClaude Haiku 5.5LLaMA 2vsClaude Haiku 5.5Gemma 1vsGPT-6.1 SolLLaMA 2vsGPT-6.1 SolGemma 1vsGrok 4.7LLaMA 2vsGrok 4.7Gemma 1vsDeepSeek-V4.1-Flash-1017LLaMA 2vsDeepSeek-V4.1-Flash-1017Gemma 1vsMistral Large 4LLaMA 2vsMistral Large 4Gemma 1vsKimi K3LLaMA 2vsKimi K3

Frequently asked questions

Gemma 1 and LLaMA 2 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. LLaMA 2 shipped 218 days before Gemma 1, so benchmark comparisons should account for the intervening progress.

Gemma 1 has 2B/7B parameters, while LLaMA 2 has 7B/13B/70B. Context windows are 8k (Gemma 1) vs 4k (LLaMA 2).

Direct benchmark comparisons are unavailable — Gemma 1 and LLaMA 2 don't publish scores on any of the same benchmarks.