mc-coa-qwen2vl-7b-2509
mc-coa-qwen2vl-7b-2509 is a 7 billion parameter image-generation model from limuyu011, released September 30, 2025. mc-coa-qwen2vl-7b-2509 is an open-weights image model with roughly 7 billion parameters.
by limuyu011 · 7B parameters
Best for
Ways to use mc-coa-qwen2vl-7b-2509 in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your limuyu011 API key. osFoundry discovers mc-coa-qwen2vl-7b-2509 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
mc-coa-qwen2vl-7b-2509 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 mc-coa-qwen2vl-7b-2509
mc-coa-qwen2vl-7b-2509 runs on a single 16GB consumer GPU (~5 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~17 GB).
mc-coa-qwen2vl-7b-2509 vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about mc-coa-qwen2vl-7b-2509
Is mc-coa-qwen2vl-7b-2509 free to use?
mc-coa-qwen2vl-7b-2509 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 mc-coa-qwen2vl-7b-2509 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 mc-coa-qwen2vl-7b-2509 need?
Approximately 5 GB at Q4 quantisation, or 17 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run mc-coa-qwen2vl-7b-2509 locally?
Yes. mc-coa-qwen2vl-7b-2509 is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is mc-coa-qwen2vl-7b-2509 best at?
mc-coa-qwen2vl-7b-2509 is well-suited to image text to text.
How do I use mc-coa-qwen2vl-7b-2509 in osFoundry?
Paste your limuyu011 API key in the key dialog (or deploy the open weights for self-hostable models), assign mc-coa-qwen2vl-7b-2509 to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by limuyu011 on September 30, 2025. Source: https://huggingface.co/limuyu011/mc-coa-qwen2vl-7b-2509