QED-Nano-SFT
Released by lm-provers in 2026, QED-Nano-SFT is an chat model. QED-Nano-SFT is an open-weights chat model.
by lm-provers
Best for
Ways to use QED-Nano-SFT in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your lm-provers API key. osFoundry discovers QED-Nano-SFT 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-Nano-SFT 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-Nano-SFT vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about QED-Nano-SFT
Is QED-Nano-SFT free to use?
QED-Nano-SFT 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-Nano-SFT 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-Nano-SFT locally?
Yes. QED-Nano-SFT is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is QED-Nano-SFT best at?
QED-Nano-SFT is well-suited to text generation.
How do I use QED-Nano-SFT in osFoundry?
Paste your lm-provers API key in the key dialog (or deploy the open weights for self-hostable models), assign QED-Nano-SFT to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by lm-provers on February 12, 2026. Source: https://huggingface.co/lm-provers/QED-Nano-SFT