qwen3-coder-next-mxfp4-moe-juju
qwen3-coder-next-mxfp4-moe-juju is a chat model from storagejuju, released May 10, 2026. qwen3-coder-next-mxfp4-moe-juju is an open-weights chat model.
by storagejuju
Best for
Ways to use qwen3-coder-next-mxfp4-moe-juju in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your storagejuju API key. osFoundry discovers qwen3-coder-next-mxfp4-moe-juju 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
qwen3-coder-next-mxfp4-moe-juju 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.
qwen3-coder-next-mxfp4-moe-juju vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about qwen3-coder-next-mxfp4-moe-juju
Is qwen3-coder-next-mxfp4-moe-juju free to use?
qwen3-coder-next-mxfp4-moe-juju 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 qwen3-coder-next-mxfp4-moe-juju 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 qwen3-coder-next-mxfp4-moe-juju locally?
Yes. qwen3-coder-next-mxfp4-moe-juju is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is qwen3-coder-next-mxfp4-moe-juju best at?
qwen3-coder-next-mxfp4-moe-juju is well-suited to text generation.
How do I use qwen3-coder-next-mxfp4-moe-juju in osFoundry?
Paste your storagejuju API key in the key dialog (or deploy the open weights for self-hostable models), assign qwen3-coder-next-mxfp4-moe-juju to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by storagejuju on May 10, 2026. Source: https://huggingface.co/storagejuju/qwen3-coder-next-mxfp4-moe-juju