WanVideo_comfy_fp8_scaled Locally (No Cloud) One-Click Setup Step-by-Step

Running this model locally is fastest when deployed through Docker.

Please follow the instructions listed below to get started.

Then, run the build command to initialize the Docker container.

📤 Release Hash: 0f92643b7d64175d25f6c1c872e05ed5 • 📅 Date: 2026-06-27 Verify Processor: next-gen chip for heavy context processing RAM: high-speed DDR5 memory preferred for CPU offloading Disk Space: 100 GB for multi-modal model vision components GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats

The WanVideo_comfy_fp8_scaled model leverages a refined FP8 quantization scheme to deliver high‑fidelity video generation while reducing memory footprint. It supports up to 1920×1080 resolution at 30 fps, enabling smooth playback for a wide range of creative workflows. By integrating a comfy diffusion backbone, the model achieves faster inference times without sacrificing visual coherence. A dedicated scaling layer ensures consistent quality across diverse content types, from cinematic scenes to everyday footage. The accompanying technical table below summarizes key performance metrics and hardware requirements for optimal deployment.

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