Huihui4-48B-A4B-vmlx-fp16
Huihui4-48B-A4B-vmlx-fp16 (LibraxisAI, 2026) is a 48 billion parameter image-generation model. Huihui4-48B-A4B-vmlx-fp16 is an open-weights image model with roughly 48 billion parameters.
by LibraxisAI · 48B parameters
Best for
Ways to use Huihui4-48B-A4B-vmlx-fp16 in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your LibraxisAI API key. osFoundry discovers Huihui4-48B-A4B-vmlx-fp16 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
Huihui4-48B-A4B-vmlx-fp16 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 Huihui4-48B-A4B-vmlx-fp16
Huihui4-48B-A4B-vmlx-fp16 runs on a single A100 40GB at Q4 quantisation (~29 GB VRAM with KV-cache headroom). Full-precision inference requires an H200 141GB or 2x A100 80GB at FP16 (~116 GB).
Huihui4-48B-A4B-vmlx-fp16 vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Huihui4-48B-A4B-vmlx-fp16
Is Huihui4-48B-A4B-vmlx-fp16 free to use?
Huihui4-48B-A4B-vmlx-fp16 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 Huihui4-48B-A4B-vmlx-fp16 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 Huihui4-48B-A4B-vmlx-fp16 need?
Approximately 29 GB at Q4 quantisation, or 116 GB at full FP16 precision. Fits on a single A100/H100 80GB.
Can I run Huihui4-48B-A4B-vmlx-fp16 locally?
Yes. Huihui4-48B-A4B-vmlx-fp16 is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Huihui4-48B-A4B-vmlx-fp16 best at?
Huihui4-48B-A4B-vmlx-fp16 is well-suited to image text to text.
How do I use Huihui4-48B-A4B-vmlx-fp16 in osFoundry?
Paste your LibraxisAI API key in the key dialog (or deploy the open weights for self-hostable models), assign Huihui4-48B-A4B-vmlx-fp16 to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by LibraxisAI on April 27, 2026. Source: https://huggingface.co/LibraxisAI/Huihui4-48B-A4B-vmlx-fp16