medgemma-27b-text-it-W4A16-G128
unaizulaika's medgemma-27b-text-it-W4A16-G128 packs 27 billion parameters into a chat model. medgemma-27b-text-it-W4A16-G128 is an open-weights chat model with roughly 27 billion parameters.
by unaizulaika · 27B parameters
Best for
- low-latency chat and routing
- request routing and triage
- text classification
Ways to use medgemma-27b-text-it-W4A16-G128 in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your unaizulaika API key. osFoundry discovers medgemma-27b-text-it-W4A16-G128 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
medgemma-27b-text-it-W4A16-G128 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 medgemma-27b-text-it-W4A16-G128
medgemma-27b-text-it-W4A16-G128 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).
medgemma-27b-text-it-W4A16-G128 vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about medgemma-27b-text-it-W4A16-G128
Is medgemma-27b-text-it-W4A16-G128 free to use?
medgemma-27b-text-it-W4A16-G128 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 medgemma-27b-text-it-W4A16-G128 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 medgemma-27b-text-it-W4A16-G128 need?
Approximately 17 GB at Q4 quantisation, or 65 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run medgemma-27b-text-it-W4A16-G128 locally?
Yes. medgemma-27b-text-it-W4A16-G128 is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is medgemma-27b-text-it-W4A16-G128 best at?
medgemma-27b-text-it-W4A16-G128 is well-suited to low-latency chat and routing, request routing and triage, text classification.
How do I use medgemma-27b-text-it-W4A16-G128 in osFoundry?
Paste your unaizulaika API key in the key dialog (or deploy the open weights for self-hostable models), assign medgemma-27b-text-it-W4A16-G128 to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by unaizulaika on March 11, 2026. Source: https://huggingface.co/unaizulaika/medgemma-27b-text-it-W4A16-G128