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.
123B70B
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
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.
$2.00Mistral—
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
$6.00Mistral—
$700Mistral—
Overview
CompanyMistralNVIDIA
Release dateJul 24 2024Oct 15 2024
AccessOpen WeightOpen Weight
Model detailsView modelView model

Frequently asked questions

Mistral Large 2 and Llama 3.1 Nemotron 70B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Mistral Large 2 shipped 83 days before Llama 3.1 Nemotron 70B, so benchmark comparisons should account for the intervening progress.

Mistral Large 2 has 123B parameters, while Llama 3.1 Nemotron 70B has 70B. Context windows are 128k (Mistral Large 2) vs 128k (Llama 3.1 Nemotron 70B).

Direct benchmark comparisons are unavailable — Mistral Large 2 and Llama 3.1 Nemotron 70B don't publish scores on any of the same benchmarks.