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.
—80B
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.
40k256k
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 dateJun 10 2025Sep 11 2025
AccessClosedOpen Weight
Model detailsView modelView model

Other comparisons

Magistral MediumvsClaude Haiku 5.5Qwen3-NextvsClaude Haiku 5.5Magistral MediumvsGPT-6.1 SolQwen3-NextvsGPT-6.1 SolMagistral MediumvsGemini 4 ArgonQwen3-NextvsGemini 4 ArgonMagistral MediumvsMuse Spark OpenQwen3-NextvsMuse Spark OpenMagistral MediumvsGrok 4.7Qwen3-NextvsGrok 4.7Magistral MediumvsDeepSeek-V4.1-Flash-1017Qwen3-NextvsDeepSeek-V4.1-Flash-1017

Frequently asked questions

Magistral Medium and Qwen3-Next don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Magistral Medium shipped 93 days before Qwen3-Next, so benchmark comparisons should account for the intervening progress.

Context windows are 40k (Magistral Medium) vs 256k (Qwen3-Next). Magistral Medium is closed, while Qwen3-Next is open weight.

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