panda-72M
Released by GilpinLab in 2025, panda-72M is an chat model. panda-72M is an open-weights chat model.
by GilpinLab
Best for
- low-latency chat and routing
- request routing and triage
- text classification
Ways to use panda-72M in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your GilpinLab API key. osFoundry discovers panda-72M 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
panda-72M 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.
panda-72M vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about panda-72M
Is panda-72M free to use?
panda-72M 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 panda-72M 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 panda-72M locally?
Yes. panda-72M is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is panda-72M best at?
panda-72M is well-suited to low-latency chat and routing, request routing and triage, text classification.
How do I use panda-72M in osFoundry?
Paste your GilpinLab API key in the key dialog (or deploy the open weights for self-hostable models), assign panda-72M to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by GilpinLab on July 9, 2025. Source: https://huggingface.co/GilpinLab/panda-72M