Kimi-K2.5-W4A8
Released by amd in 2026, Kimi-K2.5-W4A8 is an image-generation model. Kimi-K2.5-W4A8 is an open-weights image model.
by amd
Best for
Ways to use Kimi-K2.5-W4A8 in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your amd API key. osFoundry discovers Kimi-K2.5-W4A8 automatically — assign it to a Maestro role (router, direct, orchestrator, or fallback) in the Pipeline tab and it is live in every chat. Your key, your provider account — no token markup.
Deploy a dedicated endpoint
Kimi-K2.5-W4A8 is open-weights — run it locally for free, or deploy a dedicated GPU endpoint in your workspace for reserved capacity with no rate limits.
Use it in a Room App
Room Apps declare AI features in their manifest, then call them with invokeAI:
import { invokeAI } from '@osfoundry/app-sdk'
// 'summarize' is an AI feature declared in your app manifest.
const result = await invokeAI('summarize', userText)
Call it from your own apps
Once a model is wired into your workspace you can host it as an API and reach it from your own services, scripts, or CI — outside osFoundry.
Kimi-K2.5-W4A8 vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Kimi-K2.5-W4A8
Is Kimi-K2.5-W4A8 free to use?
Kimi-K2.5-W4A8 is free to run locally on your own hardware. Hosted access through osFoundry is metered (input Free (local), output Free (local)). You can switch between local and hosted at any time.
Can I use Kimi-K2.5-W4A8 commercially?
Commercial use is allowed with conditions. Licence terms not specified — verify the upstream model card before commercial use. Check upstream documentation.
Can I run Kimi-K2.5-W4A8 locally?
Yes. Kimi-K2.5-W4A8 is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Kimi-K2.5-W4A8 best at?
Kimi-K2.5-W4A8 is well-suited to image text to text.
How do I use Kimi-K2.5-W4A8 in osFoundry?
Paste your amd API key in the key dialog (or deploy the open weights for self-hostable models), assign Kimi-K2.5-W4A8 to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by amd on February 6, 2026. Source: https://huggingface.co/amd/Kimi-K2.5-W4A8