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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.
70B8B/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.
16k8k
Overview
CompanyMetaMeta
Release dateJan 29 2024Apr 18 2024
AccessOpen WeightOpen Weight
Model detailsView modelView model

Other comparisons

Code Llama 70BvsClaude Haiku 5.5LLaMA 3 (8B/70B)vsClaude Haiku 5.5Code Llama 70BvsGPT-6.1 SolLLaMA 3 (8B/70B)vsGPT-6.1 SolCode Llama 70BvsGemini 4 ArgonLLaMA 3 (8B/70B)vsGemini 4 ArgonCode Llama 70BvsGrok 4.7LLaMA 3 (8B/70B)vsGrok 4.7Code Llama 70BvsDeepSeek-V4.1-Flash-1017LLaMA 3 (8B/70B)vsDeepSeek-V4.1-Flash-1017Code Llama 70BvsMistral Large 4LLaMA 3 (8B/70B)vsMistral Large 4

Frequently asked questions

Code Llama 70B and LLaMA 3 (8B/70B) don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Code Llama 70B shipped 80 days before LLaMA 3 (8B/70B), so benchmark comparisons should account for the intervening progress.

Code Llama 70B has 70B parameters, while LLaMA 3 (8B/70B) has 8B/70B. Context windows are 16k (Code Llama 70B) vs 8k (LLaMA 3 (8B/70B)).

Direct benchmark comparisons are unavailable — Code Llama 70B and LLaMA 3 (8B/70B) don't publish scores on any of the same benchmarks.