gemma-3-1b-it-a16w4
Released by simaai in 2025, gemma-3-1b-it-a16w4 is a 1 billion parameter chat model. gemma-3-1b-it-a16w4 is an open-weights chat model with roughly 1 billion parameters.
by simaai · 1B parameters
Best for
Ways to use gemma-3-1b-it-a16w4 in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your simaai API key. osFoundry discovers gemma-3-1b-it-a16w4 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-3-1b-it-a16w4 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-3-1b-it-a16w4
gemma-3-1b-it-a16w4 runs on a single 16GB consumer GPU (~1 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~3 GB).
gemma-3-1b-it-a16w4 vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about gemma-3-1b-it-a16w4
Is gemma-3-1b-it-a16w4 free to use?
gemma-3-1b-it-a16w4 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-3-1b-it-a16w4 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-3-1b-it-a16w4 need?
Approximately 1 GB at Q4 quantisation, or 3 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run gemma-3-1b-it-a16w4 locally?
Yes. gemma-3-1b-it-a16w4 is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is gemma-3-1b-it-a16w4 best at?
gemma-3-1b-it-a16w4 is well-suited to text generation.
How do I use gemma-3-1b-it-a16w4 in osFoundry?
Paste your simaai API key in the key dialog (or deploy the open weights for self-hostable models), assign gemma-3-1b-it-a16w4 to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by simaai on October 27, 2025. Source: https://huggingface.co/simaai/gemma-3-1b-it-a16w4