ORPO8000Vikhr-Llama-3.2-1B-Instruct30002000
alexxbobr's ORPO8000Vikhr-Llama-3.2-1B-Instruct30002000 packs 1 billion parameters into a chat model. ORPO8000Vikhr-Llama-3.2-1B-Instruct30002000 is an open-weights chat model with roughly 1 billion parameters.
by alexxbobr · 1B parameters
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Ways to use ORPO8000Vikhr-Llama-3.2-1B-Instruct30002000 in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your alexxbobr API key. osFoundry discovers ORPO8000Vikhr-Llama-3.2-1B-Instruct30002000 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
ORPO8000Vikhr-Llama-3.2-1B-Instruct30002000 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 ORPO8000Vikhr-Llama-3.2-1B-Instruct30002000
ORPO8000Vikhr-Llama-3.2-1B-Instruct30002000 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).
ORPO8000Vikhr-Llama-3.2-1B-Instruct30002000 vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about ORPO8000Vikhr-Llama-3.2-1B-Instruct30002000
Is ORPO8000Vikhr-Llama-3.2-1B-Instruct30002000 free to use?
ORPO8000Vikhr-Llama-3.2-1B-Instruct30002000 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 ORPO8000Vikhr-Llama-3.2-1B-Instruct30002000 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 ORPO8000Vikhr-Llama-3.2-1B-Instruct30002000 need?
Approximately 1 GB at Q4 quantisation, or 3 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run ORPO8000Vikhr-Llama-3.2-1B-Instruct30002000 locally?
Yes. ORPO8000Vikhr-Llama-3.2-1B-Instruct30002000 is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is ORPO8000Vikhr-Llama-3.2-1B-Instruct30002000 best at?
ORPO8000Vikhr-Llama-3.2-1B-Instruct30002000 is well-suited to text generation.
How do I use ORPO8000Vikhr-Llama-3.2-1B-Instruct30002000 in osFoundry?
Paste your alexxbobr API key in the key dialog (or deploy the open weights for self-hostable models), assign ORPO8000Vikhr-Llama-3.2-1B-Instruct30002000 to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by alexxbobr on April 24, 2026. Source: https://huggingface.co/alexxbobr/ORPO8000Vikhr-Llama-3.2-1B-Instruct30002000