gemma-2-9b-synthetic_coding
gemma-2-9b-synthetic_coding is a 9 billion parameter chat model from testmoto, released December 14, 2024. gemma-2-9b-synthetic_coding is an open-weights chat model with roughly 9 billion parameters.
by testmoto · 9B parameters
Best for
Ways to use gemma-2-9b-synthetic_coding in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your testmoto API key. osFoundry discovers gemma-2-9b-synthetic_coding 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-2-9b-synthetic_coding 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-2-9b-synthetic_coding
gemma-2-9b-synthetic_coding runs on a single 16GB consumer GPU (~6 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~22 GB).
gemma-2-9b-synthetic_coding vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about gemma-2-9b-synthetic_coding
Is gemma-2-9b-synthetic_coding free to use?
gemma-2-9b-synthetic_coding 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-2-9b-synthetic_coding 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-2-9b-synthetic_coding need?
Approximately 6 GB at Q4 quantisation, or 22 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run gemma-2-9b-synthetic_coding locally?
Yes. gemma-2-9b-synthetic_coding is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is gemma-2-9b-synthetic_coding best at?
gemma-2-9b-synthetic_coding is well-suited to text generation.
How do I use gemma-2-9b-synthetic_coding in osFoundry?
Paste your testmoto API key in the key dialog (or deploy the open weights for self-hostable models), assign gemma-2-9b-synthetic_coding to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by testmoto on December 14, 2024. Source: https://huggingface.co/testmoto/gemma-2-9b-synthetic_coding