AI Model Release Tracker

Compare AI models

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.
7B/13B/34B340B
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.
16k4k
Overview
CompanyMetaNVIDIA
Release dateAug 24 2023Jun 14 2024
AccessOpen WeightOpen Weight
Model detailsView modelView model

Other comparisons

Code LlamavsClaude Haiku 5.5Nemotron-4 340BvsClaude Haiku 5.5Code LlamavsGPT-6.1 SolNemotron-4 340BvsGPT-6.1 SolCode LlamavsGemini 4 ArgonNemotron-4 340BvsGemini 4 ArgonCode LlamavsGrok 4.7Nemotron-4 340BvsGrok 4.7Code LlamavsDeepSeek-V4.1-Flash-1017Nemotron-4 340BvsDeepSeek-V4.1-Flash-1017Code LlamavsMistral Large 4Nemotron-4 340BvsMistral Large 4

Frequently asked questions

Code Llama and Nemotron-4 340B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Code Llama shipped 295 days before Nemotron-4 340B, so benchmark comparisons should account for the intervening progress.

Code Llama has 7B/13B/34B parameters, while Nemotron-4 340B has 340B. Context windows are 16k (Code Llama) vs 4k (Nemotron-4 340B).

Direct benchmark comparisons are unavailable — Code Llama and Nemotron-4 340B don't publish scores on any of the same benchmarks.