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/34B30B
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.
16k1M
API pricingUSD per 1M tokens · lower wins
Cheapest inputLowest input rate across every provider on OpenRouter, the lab included. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page.
—$0.025Darkbloom
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
—$0.12Darkbloom
—$11.00Darkbloom · int4
These models have no shared benchmark scores.
Overview
CompanyMetaNVIDIA
Release dateAug 24 2023Aug 11 2026
AccessOpen WeightOpen Source
Model detailsView modelView model

Frequently asked questions

Code Llama and Nemotron 3.5 Lightning don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Code Llama shipped 1083 days before Nemotron 3.5 Lightning, so benchmark comparisons should account for the intervening progress.

Code Llama has 7B/13B/34B parameters, while Nemotron 3.5 Lightning has 30B. Context windows are 16k (Code Llama) vs 1M (Nemotron 3.5 Lightning). Code Llama is open weight, while Nemotron 3.5 Lightning is open source.

Direct benchmark comparisons are unavailable — Code Llama and Nemotron 3.5 Lightning don't publish scores on any of the same benchmarks.