bge-m3-onnx-int8
bge-m3-onnx-int8 is a embedding model from gpahal, released June 25, 2025. bge-m3-onnx-int8 is an open-weights embed model.
by gpahal
Best for
Ways to use bge-m3-onnx-int8 in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your gpahal API key. osFoundry discovers bge-m3-onnx-int8 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
bge-m3-onnx-int8 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.
bge-m3-onnx-int8 vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about bge-m3-onnx-int8
Is bge-m3-onnx-int8 free to use?
bge-m3-onnx-int8 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 bge-m3-onnx-int8 commercially?
Commercial use is allowed with conditions. Licence terms not specified — verify the upstream model card before commercial use. Check upstream documentation.
Can I run bge-m3-onnx-int8 locally?
Yes. bge-m3-onnx-int8 is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is bge-m3-onnx-int8 best at?
bge-m3-onnx-int8 is well-suited to feature extraction.
How do I use bge-m3-onnx-int8 in osFoundry?
Paste your gpahal API key in the key dialog (or deploy the open weights for self-hostable models), assign bge-m3-onnx-int8 to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by gpahal on June 25, 2025. Source: https://huggingface.co/gpahal/bge-m3-onnx-int8