SmolLM3-3B-distilled-py-tools
Built by rdubwiley, SmolLM3-3B-distilled-py-tools is a 3 billion parameter chat model. SmolLM3-3B-distilled-py-tools is an open-weights chat model with roughly 3 billion parameters.
by rdubwiley · 3B parameters
Best for
Ways to use SmolLM3-3B-distilled-py-tools in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your rdubwiley API key. osFoundry discovers SmolLM3-3B-distilled-py-tools 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
SmolLM3-3B-distilled-py-tools 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 SmolLM3-3B-distilled-py-tools
SmolLM3-3B-distilled-py-tools runs on a single 16GB consumer GPU (~2 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~8 GB).
SmolLM3-3B-distilled-py-tools vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about SmolLM3-3B-distilled-py-tools
Is SmolLM3-3B-distilled-py-tools free to use?
SmolLM3-3B-distilled-py-tools 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 SmolLM3-3B-distilled-py-tools 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 SmolLM3-3B-distilled-py-tools need?
Approximately 2 GB at Q4 quantisation, or 8 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run SmolLM3-3B-distilled-py-tools locally?
Yes. SmolLM3-3B-distilled-py-tools is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is SmolLM3-3B-distilled-py-tools best at?
SmolLM3-3B-distilled-py-tools is well-suited to text generation.
How do I use SmolLM3-3B-distilled-py-tools in osFoundry?
Paste your rdubwiley API key in the key dialog (or deploy the open weights for self-hostable models), assign SmolLM3-3B-distilled-py-tools to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by rdubwiley on May 8, 2026. Source: https://huggingface.co/rdubwiley/SmolLM3-3B-distilled-py-tools