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.
70B22B
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.
$0.10DeepInfra—
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
$0.32DeepInfra—
$36.00DeepInfra · turbo · fp8—
Overview
CompanyMetaMistral
Release dateDec 6 2024May 29 2024
AccessOpen WeightClosed
Model detailsView modelView model

Other comparisons

LLaMA 3.3vsClaude Haiku 5.5Codestral 22BvsClaude Haiku 5.5LLaMA 3.3vsGPT-6.1 SolCodestral 22BvsGPT-6.1 SolLLaMA 3.3vsGemini 4 ArgonCodestral 22BvsGemini 4 ArgonLLaMA 3.3vsGrok 4.7Codestral 22BvsGrok 4.7LLaMA 3.3vsDeepSeek-V4.1-Flash-1017Codestral 22BvsDeepSeek-V4.1-Flash-1017LLaMA 3.3vsKimi K3Codestral 22BvsKimi K3

Frequently asked questions

LLaMA 3.3 and Codestral 22B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Codestral 22B shipped 191 days before LLaMA 3.3, so benchmark comparisons should account for the intervening progress.

LLaMA 3.3 has 70B parameters, while Codestral 22B has 22B. Context windows are 128k (LLaMA 3.3) vs 32k (Codestral 22B). LLaMA 3.3 is open weight, while Codestral 22B is closed.

Direct benchmark comparisons are unavailable — LLaMA 3.3 and Codestral 22B don't publish scores on any of the same benchmarks.