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.
—0.5B/1.5B/3B/7B/14B/32B/72B
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.
32k128k
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.
—$0.36DeepInfra
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
—$0.40DeepInfra
—$92.00DeepInfra · fp8
Overview
CompanyMistralQwen
Release dateFeb 26 2024Sep 19 2024
AccessClosedOpen Weight
Model detailsView modelView model

Other comparisons

Mistral SmallvsClaude Haiku 5.5Qwen2.5vsClaude Haiku 5.5Mistral SmallvsGPT-6.1 SolQwen2.5vsGPT-6.1 SolMistral SmallvsGemini 4 ArgonQwen2.5vsGemini 4 ArgonMistral SmallvsMuse Spark OpenQwen2.5vsMuse Spark OpenMistral SmallvsGrok 4.7Qwen2.5vsGrok 4.7Mistral SmallvsDeepSeek-V4.1-Flash-1017Qwen2.5vsDeepSeek-V4.1-Flash-1017

Frequently asked questions

Mistral Small and Qwen2.5 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Mistral Small shipped 206 days before Qwen2.5, so benchmark comparisons should account for the intervening progress.

Context windows are 32k (Mistral Small) vs 128k (Qwen2.5). Mistral Small is closed, while Qwen2.5 is open weight.

Direct benchmark comparisons are unavailable — Mistral Small and Qwen2.5 don't publish scores on any of the same benchmarks.