LTXDreamly
Built by Amador1989, LTXDreamly is an image-generation model. LTXDreamly is an open-weights image model.
by Amador1989
Best for
Ways to use LTXDreamly in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your Amador1989 API key. osFoundry discovers LTXDreamly 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
LTXDreamly 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.
LTXDreamly vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about LTXDreamly
Is LTXDreamly free to use?
LTXDreamly 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 LTXDreamly 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 LTXDreamly locally?
Yes. LTXDreamly is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is LTXDreamly best at?
LTXDreamly is well-suited to text to image.
How do I use LTXDreamly in osFoundry?
Paste your Amador1989 API key in the key dialog (or deploy the open weights for self-hostable models), assign LTXDreamly to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by Amador1989 on April 20, 2026. Source: https://huggingface.co/Amador1989/LTXDreamly