Llama-3.2-3B-Hebrew-Master
Llama-3.2-3B-Hebrew-Master is a 3 billion parameter chat model from yonioz123, released January 19, 2026. Llama-3.2-3B-Hebrew-Master is an open-weights chat model with roughly 3 billion parameters.
by yonioz123 · 3B parameters
Best for
Ways to use Llama-3.2-3B-Hebrew-Master in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your yonioz123 API key. osFoundry discovers Llama-3.2-3B-Hebrew-Master 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
Llama-3.2-3B-Hebrew-Master 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 Llama-3.2-3B-Hebrew-Master
Llama-3.2-3B-Hebrew-Master runs on a single 16GB consumer GPU (~2 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~8 GB).
Llama-3.2-3B-Hebrew-Master vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Llama-3.2-3B-Hebrew-Master
Is Llama-3.2-3B-Hebrew-Master free to use?
Llama-3.2-3B-Hebrew-Master 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 Llama-3.2-3B-Hebrew-Master 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 Llama-3.2-3B-Hebrew-Master need?
Approximately 2 GB at Q4 quantisation, or 8 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run Llama-3.2-3B-Hebrew-Master locally?
Yes. Llama-3.2-3B-Hebrew-Master is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Llama-3.2-3B-Hebrew-Master best at?
Llama-3.2-3B-Hebrew-Master is well-suited to text generation.
How do I use Llama-3.2-3B-Hebrew-Master in osFoundry?
Paste your yonioz123 API key in the key dialog (or deploy the open weights for self-hostable models), assign Llama-3.2-3B-Hebrew-Master to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by yonioz123 on January 19, 2026. Source: https://huggingface.co/yonioz123/Llama-3.2-3B-Hebrew-Master