medgemma-1.5-4b-it-NPU2
Built by FastFlowLM, medgemma-1.5-4b-it-NPU2 is a 4 billion parameter image-generation model. medgemma-1.5-4b-it-NPU2 is an open-weights image model with roughly 4 billion parameters.
by FastFlowLM · 4B parameters
Best for
Ways to use medgemma-1.5-4b-it-NPU2 in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your FastFlowLM API key. osFoundry discovers medgemma-1.5-4b-it-NPU2 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-1.5-4b-it-NPU2 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-1.5-4b-it-NPU2
medgemma-1.5-4b-it-NPU2 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).
medgemma-1.5-4b-it-NPU2 vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about medgemma-1.5-4b-it-NPU2
Is medgemma-1.5-4b-it-NPU2 free to use?
medgemma-1.5-4b-it-NPU2 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-1.5-4b-it-NPU2 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-1.5-4b-it-NPU2 need?
Approximately 3 GB at Q4 quantisation, or 10 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run medgemma-1.5-4b-it-NPU2 locally?
Yes. medgemma-1.5-4b-it-NPU2 is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is medgemma-1.5-4b-it-NPU2 best at?
medgemma-1.5-4b-it-NPU2 is well-suited to image text to text.
How do I use medgemma-1.5-4b-it-NPU2 in osFoundry?
Paste your FastFlowLM API key in the key dialog (or deploy the open weights for self-hostable models), assign medgemma-1.5-4b-it-NPU2 to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by FastFlowLM on February 18, 2026. Source: https://huggingface.co/FastFlowLM/medgemma-1.5-4b-it-NPU2