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.
12B80B
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.
128k256k
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.
—$0.072DeepInfra
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
—$0.88DeepInfra
—$73.00DeepInfra · fp8
Overview
CompanyMistralQwen
Release dateSep 11 2024Sep 11 2025
AccessOpen WeightOpen Weight
Model detailsView modelView model

Other comparisons

Pixtral 24.09vsClaude Haiku 5.5Qwen3-NextvsClaude Haiku 5.5Pixtral 24.09vsGPT-6.1 SolQwen3-NextvsGPT-6.1 SolPixtral 24.09vsGemini 4 ArgonQwen3-NextvsGemini 4 ArgonPixtral 24.09vsMuse Spark OpenQwen3-NextvsMuse Spark OpenPixtral 24.09vsGrok 4.7Qwen3-NextvsGrok 4.7Pixtral 24.09vsDeepSeek-V4.1-Flash-1017Qwen3-NextvsDeepSeek-V4.1-Flash-1017

Frequently asked questions

Pixtral 24.09 and Qwen3-Next don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Pixtral 24.09 shipped 365 days before Qwen3-Next, so benchmark comparisons should account for the intervening progress.

Pixtral 24.09 has 12B parameters, while Qwen3-Next has 80B. Context windows are 128k (Pixtral 24.09) vs 256k (Qwen3-Next).

Direct benchmark comparisons are unavailable — Pixtral 24.09 and Qwen3-Next don't publish scores on any of the same benchmarks.