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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/49B
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.
16k128k
Overview
CompanyMetaNVIDIA
Release dateJan 29 2024Mar 18 2025
AccessOpen WeightOpen Weight
Model detailsView modelView model

Other comparisons

Code Llama 70BvsClaude Haiku 5.5Llama Nemotron (Nano/Super)vsClaude Haiku 5.5Code Llama 70BvsGPT-6.1 SolLlama Nemotron (Nano/Super)vsGPT-6.1 SolCode Llama 70BvsGemini 4 ArgonLlama Nemotron (Nano/Super)vsGemini 4 ArgonCode Llama 70BvsGrok 4.7Llama Nemotron (Nano/Super)vsGrok 4.7Code Llama 70BvsDeepSeek-V4.1-Flash-1017Llama Nemotron (Nano/Super)vsDeepSeek-V4.1-Flash-1017Code Llama 70BvsMistral Large 4Llama Nemotron (Nano/Super)vsMistral Large 4

Frequently asked questions

Code Llama 70B and Llama Nemotron (Nano/Super) don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Code Llama 70B shipped 414 days before Llama Nemotron (Nano/Super), so benchmark comparisons should account for the intervening progress.

Code Llama 70B has 70B parameters, while Llama Nemotron (Nano/Super) has 8B/49B. Context windows are 16k (Code Llama 70B) vs 128k (Llama Nemotron (Nano/Super)).

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