QED-75M
QED-75M is a chat model from levossadtchi, released March 19, 2026. QED-75M is an open-weights chat model.
by levossadtchi
Best for
Ways to use QED-75M in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your levossadtchi API key. osFoundry discovers QED-75M 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
QED-75M 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.
QED-75M vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about QED-75M
Is QED-75M free to use?
QED-75M 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 QED-75M 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 QED-75M locally?
Yes. QED-75M is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is QED-75M best at?
QED-75M is well-suited to text generation.
How do I use QED-75M in osFoundry?
Paste your levossadtchi API key in the key dialog (or deploy the open weights for self-hostable models), assign QED-75M to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by levossadtchi on March 19, 2026. Source: https://huggingface.co/levossadtchi/QED-75M