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.
1B/3B/11B/90B—
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.
128k32k
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.
$0.027Cloudflare—
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
$0.201Cloudflare—
$15.45Cloudflare—
Overview
CompanyMetaMistral
Release dateSep 25 2024Dec 11 2023
AccessOpen WeightClosed
Model detailsView modelView model

Other comparisons

LLaMA 3.2vsClaude Haiku 5.5Mistral MediumvsClaude Haiku 5.5LLaMA 3.2vsGPT-6.1 SolMistral MediumvsGPT-6.1 SolLLaMA 3.2vsGemini 4 ArgonMistral MediumvsGemini 4 ArgonLLaMA 3.2vsGrok 4.7Mistral MediumvsGrok 4.7LLaMA 3.2vsDeepSeek-V4.1-Flash-1017Mistral MediumvsDeepSeek-V4.1-Flash-1017LLaMA 3.2vsKimi K3Mistral MediumvsKimi K3

Frequently asked questions

LLaMA 3.2 and Mistral Medium don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Mistral Medium shipped 289 days before LLaMA 3.2, so benchmark comparisons should account for the intervening progress.

Context windows are 128k (LLaMA 3.2) vs 32k (Mistral Medium). LLaMA 3.2 is open weight, while Mistral Medium is closed.

Direct benchmark comparisons are unavailable — LLaMA 3.2 and Mistral Medium don't publish scores on any of the same benchmarks.