Baichuan-M2-32B-GPTQ-Int4
baichuan-inc's Baichuan-M2-32B-GPTQ-Int4 packs 32 billion parameters into a chat model. Baichuan-M2-32B-GPTQ-Int4 is an open-weights chat model with roughly 32 billion parameters.
by baichuan-inc · 32B parameters
Best for
Ways to use Baichuan-M2-32B-GPTQ-Int4 in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your baichuan-inc API key. osFoundry discovers Baichuan-M2-32B-GPTQ-Int4 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
Baichuan-M2-32B-GPTQ-Int4 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 Baichuan-M2-32B-GPTQ-Int4
Baichuan-M2-32B-GPTQ-Int4 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).
Baichuan-M2-32B-GPTQ-Int4 vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Baichuan-M2-32B-GPTQ-Int4
Is Baichuan-M2-32B-GPTQ-Int4 free to use?
Baichuan-M2-32B-GPTQ-Int4 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 Baichuan-M2-32B-GPTQ-Int4 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 Baichuan-M2-32B-GPTQ-Int4 need?
Approximately 20 GB at Q4 quantisation, or 77 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run Baichuan-M2-32B-GPTQ-Int4 locally?
Yes. Baichuan-M2-32B-GPTQ-Int4 is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Baichuan-M2-32B-GPTQ-Int4 best at?
Baichuan-M2-32B-GPTQ-Int4 is well-suited to text generation.
How do I use Baichuan-M2-32B-GPTQ-Int4 in osFoundry?
Paste your baichuan-inc API key in the key dialog (or deploy the open weights for self-hostable models), assign Baichuan-M2-32B-GPTQ-Int4 to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by baichuan-inc on August 10, 2025. Source: https://huggingface.co/baichuan-inc/Baichuan-M2-32B-GPTQ-Int4