Gemma3-27B-it-vl-GLM-4.7-Uncensored-Heretic-Deep-Reasoning
DavidAU's Gemma3-27B-it-vl-GLM-4.7-Uncensored-Heretic-Deep-Reasoning packs 27 billion parameters into a image-generation model. Gemma3-27B-it-vl-GLM-4.7-Uncensored-Heretic-Deep-Reasoning is an open-weights image model with roughly 27 billion parameters.
by DavidAU · 27B parameters
Best for
Ways to use Gemma3-27B-it-vl-GLM-4.7-Uncensored-Heretic-Deep-Reasoning in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your DavidAU API key. osFoundry discovers Gemma3-27B-it-vl-GLM-4.7-Uncensored-Heretic-Deep-Reasoning 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
Gemma3-27B-it-vl-GLM-4.7-Uncensored-Heretic-Deep-Reasoning 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 Gemma3-27B-it-vl-GLM-4.7-Uncensored-Heretic-Deep-Reasoning
Gemma3-27B-it-vl-GLM-4.7-Uncensored-Heretic-Deep-Reasoning 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).
Gemma3-27B-it-vl-GLM-4.7-Uncensored-Heretic-Deep-Reasoning vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Gemma3-27B-it-vl-GLM-4.7-Uncensored-Heretic-Deep-Reasoning
Is Gemma3-27B-it-vl-GLM-4.7-Uncensored-Heretic-Deep-Reasoning free to use?
Gemma3-27B-it-vl-GLM-4.7-Uncensored-Heretic-Deep-Reasoning 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 Gemma3-27B-it-vl-GLM-4.7-Uncensored-Heretic-Deep-Reasoning 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 Gemma3-27B-it-vl-GLM-4.7-Uncensored-Heretic-Deep-Reasoning need?
Approximately 17 GB at Q4 quantisation, or 65 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run Gemma3-27B-it-vl-GLM-4.7-Uncensored-Heretic-Deep-Reasoning locally?
Yes. Gemma3-27B-it-vl-GLM-4.7-Uncensored-Heretic-Deep-Reasoning is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Gemma3-27B-it-vl-GLM-4.7-Uncensored-Heretic-Deep-Reasoning best at?
Gemma3-27B-it-vl-GLM-4.7-Uncensored-Heretic-Deep-Reasoning is well-suited to image text to text.
How do I use Gemma3-27B-it-vl-GLM-4.7-Uncensored-Heretic-Deep-Reasoning in osFoundry?
Paste your DavidAU API key in the key dialog (or deploy the open weights for self-hostable models), assign Gemma3-27B-it-vl-GLM-4.7-Uncensored-Heretic-Deep-Reasoning to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by DavidAU on January 26, 2026. Source: https://huggingface.co/DavidAU/Gemma3-27B-it-vl-GLM-4.7-Uncensored-Heretic-Deep-Reasoning