llama3_2-1B-deepseek
llama3_2-1B-deepseek (BarraHome, 2025) is a 1 billion parameter chat model. llama3_2-1B-deepseek is an open-weights chat model with roughly 1 billion parameters.
by BarraHome · 1B parameters
Best for
Ways to use llama3_2-1B-deepseek in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your BarraHome API key. osFoundry discovers llama3_2-1B-deepseek 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
llama3_2-1B-deepseek 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 llama3_2-1B-deepseek
llama3_2-1B-deepseek 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).
llama3_2-1B-deepseek vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about llama3_2-1B-deepseek
Is llama3_2-1B-deepseek free to use?
llama3_2-1B-deepseek 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 llama3_2-1B-deepseek 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 llama3_2-1B-deepseek need?
Approximately 1 GB at Q4 quantisation, or 3 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run llama3_2-1B-deepseek locally?
Yes. llama3_2-1B-deepseek is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is llama3_2-1B-deepseek best at?
llama3_2-1B-deepseek is well-suited to text generation.
How do I use llama3_2-1B-deepseek in osFoundry?
Paste your BarraHome API key in the key dialog (or deploy the open weights for self-hostable models), assign llama3_2-1B-deepseek to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by BarraHome on June 10, 2025. Source: https://huggingface.co/BarraHome/llama3_2-1B-deepseek