gemma-4-31b-it-oQ8
frogggias's gemma-4-31b-it-oQ8 packs 31 billion parameters into a chat model. gemma-4-31b-it-oQ8 is an open-weights chat model with roughly 31 billion parameters.
by frogggias · 31B parameters
Best for
- low-latency chat and routing
- request routing and triage
- text classification
Ways to use gemma-4-31b-it-oQ8 in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your frogggias API key. osFoundry discovers gemma-4-31b-it-oQ8 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-4-31b-it-oQ8 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-4-31b-it-oQ8
gemma-4-31b-it-oQ8 runs on a 24GB consumer or workstation GPU (~19 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~75 GB).
gemma-4-31b-it-oQ8 vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about gemma-4-31b-it-oQ8
Is gemma-4-31b-it-oQ8 free to use?
gemma-4-31b-it-oQ8 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-4-31b-it-oQ8 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-4-31b-it-oQ8 need?
Approximately 19 GB at Q4 quantisation, or 75 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run gemma-4-31b-it-oQ8 locally?
Yes. gemma-4-31b-it-oQ8 is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is gemma-4-31b-it-oQ8 best at?
gemma-4-31b-it-oQ8 is well-suited to low-latency chat and routing, request routing and triage, text classification.
How do I use gemma-4-31b-it-oQ8 in osFoundry?
Paste your frogggias API key in the key dialog (or deploy the open weights for self-hostable models), assign gemma-4-31b-it-oQ8 to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by frogggias on April 18, 2026. Source: https://huggingface.co/frogggias/gemma-4-31b-it-oQ8