Llama-3.2V-11B-cot
Llama-3.2V-11B-cot (Xkev, 2024) is a 11 billion parameter image-generation model. Llama-3.2V-11B-cot is an open-weights image model with roughly 11 billion parameters.
by Xkev · 11B parameters
Best for
Ways to use Llama-3.2V-11B-cot in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your Xkev API key. osFoundry discovers Llama-3.2V-11B-cot 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-3.2V-11B-cot 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-3.2V-11B-cot
Llama-3.2V-11B-cot runs on a single 16GB consumer GPU (~7 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~27 GB).
Llama-3.2V-11B-cot vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Llama-3.2V-11B-cot
Is Llama-3.2V-11B-cot free to use?
Llama-3.2V-11B-cot 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-3.2V-11B-cot 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-3.2V-11B-cot need?
Approximately 7 GB at Q4 quantisation, or 27 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run Llama-3.2V-11B-cot locally?
Yes. Llama-3.2V-11B-cot is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Llama-3.2V-11B-cot best at?
Llama-3.2V-11B-cot is well-suited to image text to text.
How do I use Llama-3.2V-11B-cot in osFoundry?
Paste your Xkev API key in the key dialog (or deploy the open weights for self-hostable models), assign Llama-3.2V-11B-cot to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by Xkev on November 19, 2024. Source: https://huggingface.co/Xkev/Llama-3.2V-11B-cot