flux2-klein-base-9b-distill-lora
Built by vafipas663, flux2-klein-base-9b-distill-lora is a 9 billion parameter image-generation model. flux2-klein-base-9b-distill-lora is an open-weights image model with roughly 9 billion parameters.
by vafipas663 · 9B parameters
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Ways to use flux2-klein-base-9b-distill-lora in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your vafipas663 API key. osFoundry discovers flux2-klein-base-9b-distill-lora 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
flux2-klein-base-9b-distill-lora 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 flux2-klein-base-9b-distill-lora
flux2-klein-base-9b-distill-lora runs on a single 16GB consumer GPU (~6 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~22 GB).
flux2-klein-base-9b-distill-lora vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about flux2-klein-base-9b-distill-lora
Is flux2-klein-base-9b-distill-lora free to use?
flux2-klein-base-9b-distill-lora 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 flux2-klein-base-9b-distill-lora 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 flux2-klein-base-9b-distill-lora need?
Approximately 6 GB at Q4 quantisation, or 22 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run flux2-klein-base-9b-distill-lora locally?
Yes. flux2-klein-base-9b-distill-lora is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is flux2-klein-base-9b-distill-lora best at?
flux2-klein-base-9b-distill-lora is well-suited to image to image.
How do I use flux2-klein-base-9b-distill-lora in osFoundry?
Paste your vafipas663 API key in the key dialog (or deploy the open weights for self-hostable models), assign flux2-klein-base-9b-distill-lora to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by vafipas663 on January 29, 2026. Source: https://huggingface.co/vafipas663/flux2-klein-base-9b-distill-lora