Qwen3.5-27B-MedReasoning
Qwen3.5-27B-MedReasoning is a 27 billion parameter image-generation model from Zaynoid, released February 28, 2026. Qwen3.5-27B-MedReasoning is an open-weights image model with roughly 27 billion parameters.
by Zaynoid · 27B parameters
Best for
Ways to use Qwen3.5-27B-MedReasoning in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your Zaynoid API key. osFoundry discovers Qwen3.5-27B-MedReasoning 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
Qwen3.5-27B-MedReasoning 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 Qwen3.5-27B-MedReasoning
Qwen3.5-27B-MedReasoning runs on a 24GB consumer or workstation GPU (~17 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~65 GB).
Qwen3.5-27B-MedReasoning vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Qwen3.5-27B-MedReasoning
Is Qwen3.5-27B-MedReasoning free to use?
Qwen3.5-27B-MedReasoning 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 Qwen3.5-27B-MedReasoning 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 Qwen3.5-27B-MedReasoning need?
Approximately 17 GB at Q4 quantisation, or 65 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run Qwen3.5-27B-MedReasoning locally?
Yes. Qwen3.5-27B-MedReasoning is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Qwen3.5-27B-MedReasoning best at?
Qwen3.5-27B-MedReasoning is well-suited to image text to text.
How do I use Qwen3.5-27B-MedReasoning in osFoundry?
Paste your Zaynoid API key in the key dialog (or deploy the open weights for self-hostable models), assign Qwen3.5-27B-MedReasoning to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by Zaynoid on February 28, 2026. Source: https://huggingface.co/Zaynoid/Qwen3.5-27B-MedReasoning