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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.
24B2.8T
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.
128k1M
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.
$0.075DeepInfra—
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
$0.20DeepInfra—
$25.00DeepInfra · fp8—
Overview
CompanyMistralMoonshot AI
Release dateJun 20 2025Oct 23 2026
AccessOpen WeightClosed
Model detailsView modelView model

Other comparisons

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Frequently asked questions

Mistral Small 3.2 and Kimi K3.1 Pro Highspeed don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Mistral Small 3.2 shipped 490 days before Kimi K3.1 Pro Highspeed, so benchmark comparisons should account for the intervening progress.

Mistral Small 3.2 has 24B parameters, while Kimi K3.1 Pro Highspeed has 2.8T. Context windows are 128k (Mistral Small 3.2) vs 1M (Kimi K3.1 Pro Highspeed). Mistral Small 3.2 is open weight, while Kimi K3.1 Pro Highspeed is closed.

Direct benchmark comparisons are unavailable — Mistral Small 3.2 and Kimi K3.1 Pro Highspeed don't publish scores on any of the same benchmarks.