MedusaGemma-E4B
Built by stamsam, MedusaGemma-E4B is a 4 billion parameter chat model. MedusaGemma-E4B is an open-weights chat model with roughly 4 billion parameters.
by stamsam · 4B parameters
Best for
Ways to use MedusaGemma-E4B in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your stamsam API key. osFoundry discovers MedusaGemma-E4B 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
MedusaGemma-E4B 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 MedusaGemma-E4B
MedusaGemma-E4B runs on a single 16GB consumer GPU (~3 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~10 GB).
MedusaGemma-E4B vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about MedusaGemma-E4B
Is MedusaGemma-E4B free to use?
MedusaGemma-E4B 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 MedusaGemma-E4B 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 MedusaGemma-E4B need?
Approximately 3 GB at Q4 quantisation, or 10 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run MedusaGemma-E4B locally?
Yes. MedusaGemma-E4B is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is MedusaGemma-E4B best at?
MedusaGemma-E4B is well-suited to text generation.
How do I use MedusaGemma-E4B in osFoundry?
Paste your stamsam API key in the key dialog (or deploy the open weights for self-hostable models), assign MedusaGemma-E4B to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by stamsam on April 22, 2026. Source: https://huggingface.co/stamsam/MedusaGemma-E4B