Qwen2.5-32B
Qwen's Qwen2.5-32B packs 32 billion parameters into a chat model. Qwen2.5-32B is an open-weights chat model with roughly 32 billion parameters.
by Qwen · 32B parameters
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Ways to use Qwen2.5-32B in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your Qwen API key. osFoundry discovers Qwen2.5-32B 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
Qwen2.5-32B 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 Qwen2.5-32B
Qwen2.5-32B runs on a 24GB consumer or workstation GPU (~20 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~77 GB).
Qwen2.5-32B vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Qwen2.5-32B
Is Qwen2.5-32B free to use?
Qwen2.5-32B 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 Qwen2.5-32B 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 Qwen2.5-32B need?
Approximately 20 GB at Q4 quantisation, or 77 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run Qwen2.5-32B locally?
Yes. Qwen2.5-32B is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Qwen2.5-32B best at?
Qwen2.5-32B is well-suited to text generation.
How do I use Qwen2.5-32B in osFoundry?
Paste your Qwen API key in the key dialog (or deploy the open weights for self-hostable models), assign Qwen2.5-32B to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by Qwen on September 15, 2024. Source: https://huggingface.co/Qwen/Qwen2.5-32B