Med-Asagi-14B-reasoning_beta
MIL-UT's Med-Asagi-14B-reasoning_beta packs 14 billion parameters into a image-generation model. Med-Asagi-14B-reasoning_beta is an open-weights image model with roughly 14 billion parameters.
by MIL-UT · 14B parameters
Best for
Ways to use Med-Asagi-14B-reasoning_beta in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your MIL-UT API key. osFoundry discovers Med-Asagi-14B-reasoning_beta 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
Med-Asagi-14B-reasoning_beta 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.
What hardware can run Med-Asagi-14B-reasoning_beta
Med-Asagi-14B-reasoning_beta runs on a single 16GB consumer GPU (~9 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~34 GB).
Med-Asagi-14B-reasoning_beta vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Med-Asagi-14B-reasoning_beta
Is Med-Asagi-14B-reasoning_beta free to use?
Med-Asagi-14B-reasoning_beta 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 Med-Asagi-14B-reasoning_beta commercially?
Commercial use is allowed with conditions. Licence terms not specified — verify the upstream model card before commercial use. Check upstream documentation.
How much VRAM does Med-Asagi-14B-reasoning_beta need?
Approximately 9 GB at Q4 quantisation, or 34 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run Med-Asagi-14B-reasoning_beta locally?
Yes. Med-Asagi-14B-reasoning_beta is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Med-Asagi-14B-reasoning_beta best at?
Med-Asagi-14B-reasoning_beta is well-suited to image text to text.
How do I use Med-Asagi-14B-reasoning_beta in osFoundry?
Paste your MIL-UT API key in the key dialog (or deploy the open weights for self-hostable models), assign Med-Asagi-14B-reasoning_beta to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by MIL-UT on March 10, 2026. Source: https://huggingface.co/MIL-UT/Med-Asagi-14B-reasoning_beta