llm-jp-3-150m
Released by llm-jp in 2025, llm-jp-3-150m is an chat model. llm-jp-3-150m is an open-weights chat model.
by llm-jp
Best for
Ways to use llm-jp-3-150m in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your llm-jp API key. osFoundry discovers llm-jp-3-150m 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
llm-jp-3-150m 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.
llm-jp-3-150m vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about llm-jp-3-150m
Is llm-jp-3-150m free to use?
llm-jp-3-150m 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 llm-jp-3-150m 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 llm-jp-3-150m locally?
Yes. llm-jp-3-150m is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is llm-jp-3-150m best at?
llm-jp-3-150m is well-suited to text generation.
How do I use llm-jp-3-150m in osFoundry?
Paste your llm-jp API key in the key dialog (or deploy the open weights for self-hostable models), assign llm-jp-3-150m to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by llm-jp on January 27, 2025. Source: https://huggingface.co/llm-jp/llm-jp-3-150m