Qwen3.5-0.8B-quantized_uncensored_finetuned
amkkk's Qwen3.5-0.8B-quantized_uncensored_finetuned packs 1 billion parameters into a image-generation model. Qwen3.5-0.8B-quantized_uncensored_finetuned is an open-weights image model with roughly 1 billion parameters.
by amkkk · 1B parameters
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Ways to use Qwen3.5-0.8B-quantized_uncensored_finetuned in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your amkkk API key. osFoundry discovers Qwen3.5-0.8B-quantized_uncensored_finetuned 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
Qwen3.5-0.8B-quantized_uncensored_finetuned 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 Qwen3.5-0.8B-quantized_uncensored_finetuned
Qwen3.5-0.8B-quantized_uncensored_finetuned runs on a single 16GB consumer GPU (~1 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~3 GB).
Qwen3.5-0.8B-quantized_uncensored_finetuned vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Qwen3.5-0.8B-quantized_uncensored_finetuned
Is Qwen3.5-0.8B-quantized_uncensored_finetuned free to use?
Qwen3.5-0.8B-quantized_uncensored_finetuned 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 Qwen3.5-0.8B-quantized_uncensored_finetuned 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 Qwen3.5-0.8B-quantized_uncensored_finetuned need?
Approximately 1 GB at Q4 quantisation, or 3 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run Qwen3.5-0.8B-quantized_uncensored_finetuned locally?
Yes. Qwen3.5-0.8B-quantized_uncensored_finetuned is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Qwen3.5-0.8B-quantized_uncensored_finetuned best at?
Qwen3.5-0.8B-quantized_uncensored_finetuned is well-suited to image text to text.
How do I use Qwen3.5-0.8B-quantized_uncensored_finetuned in osFoundry?
Paste your amkkk API key in the key dialog (or deploy the open weights for self-hostable models), assign Qwen3.5-0.8B-quantized_uncensored_finetuned to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by amkkk on March 6, 2026. Source: https://huggingface.co/amkkk/Qwen3.5-0.8B-quantized_uncensored_finetuned