Slider-toolkit-Klein4B
Built by NO8D, Slider-toolkit-Klein4B is a 4 billion parameter image-generation model. Slider-toolkit-Klein4B is an open-weights image model with roughly 4 billion parameters.
by NO8D · 4B parameters
Best for
Ways to use Slider-toolkit-Klein4B in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your NO8D API key. osFoundry discovers Slider-toolkit-Klein4B 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
Slider-toolkit-Klein4B 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 Slider-toolkit-Klein4B
Slider-toolkit-Klein4B runs on a single 16GB consumer GPU (~3 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~10 GB).
Slider-toolkit-Klein4B vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Slider-toolkit-Klein4B
Is Slider-toolkit-Klein4B free to use?
Slider-toolkit-Klein4B 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 Slider-toolkit-Klein4B 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 Slider-toolkit-Klein4B need?
Approximately 3 GB at Q4 quantisation, or 10 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run Slider-toolkit-Klein4B locally?
Yes. Slider-toolkit-Klein4B is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Slider-toolkit-Klein4B best at?
Slider-toolkit-Klein4B is well-suited to text to image.
How do I use Slider-toolkit-Klein4B in osFoundry?
Paste your NO8D API key in the key dialog (or deploy the open weights for self-hostable models), assign Slider-toolkit-Klein4B to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by NO8D on March 4, 2026. Source: https://huggingface.co/NO8D/Slider-toolkit-Klein4B