Wan2.2-T2V-A14B-Diffusers_fp32_vae
Released by lopho in 2025, Wan2.2-T2V-A14B-Diffusers_fp32_vae is a 14 billion parameter chat model. Wan2.2-T2V-A14B-Diffusers_fp32_vae is an open-weights chat model with roughly 14 billion parameters.
by lopho · 14B parameters
Best for
- low-latency chat and routing
- request routing and triage
- text classification
Ways to use Wan2.2-T2V-A14B-Diffusers_fp32_vae in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your lopho API key. osFoundry discovers Wan2.2-T2V-A14B-Diffusers_fp32_vae 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
Wan2.2-T2V-A14B-Diffusers_fp32_vae 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 Wan2.2-T2V-A14B-Diffusers_fp32_vae
Wan2.2-T2V-A14B-Diffusers_fp32_vae runs on a single 16GB consumer GPU (~9 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~34 GB).
Wan2.2-T2V-A14B-Diffusers_fp32_vae vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Wan2.2-T2V-A14B-Diffusers_fp32_vae
Is Wan2.2-T2V-A14B-Diffusers_fp32_vae free to use?
Wan2.2-T2V-A14B-Diffusers_fp32_vae 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 Wan2.2-T2V-A14B-Diffusers_fp32_vae 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 Wan2.2-T2V-A14B-Diffusers_fp32_vae need?
Approximately 9 GB at Q4 quantisation, or 34 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run Wan2.2-T2V-A14B-Diffusers_fp32_vae locally?
Yes. Wan2.2-T2V-A14B-Diffusers_fp32_vae is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Wan2.2-T2V-A14B-Diffusers_fp32_vae best at?
Wan2.2-T2V-A14B-Diffusers_fp32_vae is well-suited to low-latency chat and routing, request routing and triage, text classification.
How do I use Wan2.2-T2V-A14B-Diffusers_fp32_vae in osFoundry?
Paste your lopho API key in the key dialog (or deploy the open weights for self-hostable models), assign Wan2.2-T2V-A14B-Diffusers_fp32_vae to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by lopho on August 9, 2025. Source: https://huggingface.co/lopho/Wan2.2-T2V-A14B-Diffusers_fp32_vae