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.
8B/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.
128k128k
API pricingUSD per 1M tokens · lower wins
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it.
—$15.00
Output priceWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one.
—$60.00
Cached input priceA reduced rate for text you send over and over. If every request starts with the same instructions or the same document, the provider keeps a copy ready and charges less to read it again.
—$7.50
—$6,000OpenAI list price
These models have no shared benchmark scores.
Overview
CompanyNVIDIAOpenAI
Release dateMar 18 2025Sep 12 2024
AccessOpen WeightClosed
Model detailsView modelView model

Frequently asked questions

Llama Nemotron (Nano/Super) and o1-preview don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only o1-preview has a verified first-party API price: $15.00 per million input tokens and $60.00 per million output tokens. No pay-as-you-go API rate is tracked for Llama Nemotron (Nano/Super). o1-preview shipped 187 days before Llama Nemotron (Nano/Super), so benchmark comparisons should account for the intervening progress.

Context windows are 128k (Llama Nemotron (Nano/Super)) vs 128k (o1-preview). Llama Nemotron (Nano/Super) is open weight, while o1-preview is closed.

Direct benchmark comparisons are unavailable — Llama Nemotron (Nano/Super) and o1-preview don't publish scores on any of the same benchmarks.