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.
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.
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.
—$1.10
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.
—$4.40
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.
—$0.55
—$440OpenAI list price
These models have no shared benchmark scores.
Overview
CompanyNVIDIAOpenAI
Release dateOct 15 2024Sep 12 2024
AccessOpen WeightClosed
Model detailsView modelView model

Frequently asked questions

Llama 3.1 Nemotron 70B and o1-mini don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only o1-mini has a verified first-party API price: $1.10 per million input tokens and $4.40 per million output tokens. No pay-as-you-go API rate is tracked for Llama 3.1 Nemotron 70B. o1-mini shipped 33 days before Llama 3.1 Nemotron 70B, so benchmark comparisons should account for the intervening progress.

Context windows are 128k (Llama 3.1 Nemotron 70B) vs 128k (o1-mini). Llama 3.1 Nemotron 70B is open weight, while o1-mini is closed.

Direct benchmark comparisons are unavailable — Llama 3.1 Nemotron 70B and o1-mini don't publish scores on any of the same benchmarks.