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/34B123B
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.
16k128k
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
CompanyMetaMistral
Release dateAug 24 2023Jul 24 2024
AccessOpen WeightOpen Weight
Model detailsView modelView model

Other comparisons

Code LlamavsClaude Haiku 5.5Mistral Large 2vsClaude Haiku 5.5Code LlamavsGPT-6.1 SolMistral Large 2vsGPT-6.1 SolCode LlamavsGemini 4 ArgonMistral Large 2vsGemini 4 ArgonCode LlamavsGrok 4.7Mistral Large 2vsGrok 4.7Code LlamavsDeepSeek-V4.1-Flash-1017Mistral Large 2vsDeepSeek-V4.1-Flash-1017Code LlamavsKimi K3Mistral Large 2vsKimi K3

Frequently asked questions

Code Llama and Mistral Large 2 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Code Llama shipped 335 days before Mistral Large 2, so benchmark comparisons should account for the intervening progress.

Code Llama has 7B/13B/34B parameters, while Mistral Large 2 has 123B. Context windows are 16k (Code Llama) vs 128k (Mistral Large 2).

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