AI Model Release Tracker

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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.
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$2.00Mistral
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
$0.32DeepInfra$6.00Mistral
$36.00DeepInfra · turbo · fp8$700Mistral
Overview
CompanyMetaMistral
Release dateDec 6 2024Feb 26 2024
AccessOpen WeightClosed
Model detailsView modelView model

Other comparisons

LLaMA 3.3vsClaude Haiku 5.5Mistral LargevsClaude Haiku 5.5LLaMA 3.3vsGPT-6.1 SolMistral LargevsGPT-6.1 SolLLaMA 3.3vsGemini 4 ArgonMistral LargevsGemini 4 ArgonLLaMA 3.3vsGrok 4.7Mistral LargevsGrok 4.7LLaMA 3.3vsDeepSeek-V4.1-Flash-1017Mistral LargevsDeepSeek-V4.1-Flash-1017LLaMA 3.3vsKimi K3Mistral LargevsKimi K3

Frequently asked questions

LLaMA 3.3 and Mistral Large don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Mistral Large shipped 284 days before LLaMA 3.3, so benchmark comparisons should account for the intervening progress.

Context windows are 128k (LLaMA 3.3) vs 32k (Mistral Large). LLaMA 3.3 is open weight, while Mistral Large is closed.

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