gemma-3-27b-it-INT4
gemma-3-27b-it-INT4 is a 27 billion parameter image-generation model from pytorch, released August 27, 2025. gemma-3-27b-it-INT4 is an open-weights image model with roughly 27 billion parameters.
by pytorch · 27B parameters
Best for
Ways to use gemma-3-27b-it-INT4 in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your pytorch API key. osFoundry discovers gemma-3-27b-it-INT4 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
gemma-3-27b-it-INT4 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 gemma-3-27b-it-INT4
gemma-3-27b-it-INT4 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).
gemma-3-27b-it-INT4 vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about gemma-3-27b-it-INT4
Is gemma-3-27b-it-INT4 free to use?
gemma-3-27b-it-INT4 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 gemma-3-27b-it-INT4 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 gemma-3-27b-it-INT4 need?
Approximately 17 GB at Q4 quantisation, or 65 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run gemma-3-27b-it-INT4 locally?
Yes. gemma-3-27b-it-INT4 is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is gemma-3-27b-it-INT4 best at?
gemma-3-27b-it-INT4 is well-suited to image text to text.
How do I use gemma-3-27b-it-INT4 in osFoundry?
Paste your pytorch API key in the key dialog (or deploy the open weights for self-hostable models), assign gemma-3-27b-it-INT4 to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by pytorch on August 27, 2025. Source: https://huggingface.co/pytorch/gemma-3-27b-it-INT4