WanVideo_comfy_fp8_scaled Locally via LM Studio For Low VRAM (6GB/8GB) Windows

If you want the fastest local installation for this model, use standard pip packages.

Please follow the instructions listed below to get started.

All large files and heavy weights are downloaded automatically by the script.

Once launched, the wizard detects your specs to configure the model for maximum efficiency.

🔧 Digest: 7733761c1134fd0653f7c06f84de956a • 🕒 Updated: 2026-06-24
  • Processor: high single-core performance needed for token latency
  • RAM: 64 GB to avoid OOM crashes on large contexts
  • Disk Space:70 GB free space for full FP16 weights storage
  • GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

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.

Model WanVideo_comfy_fp8_scaled
Parameters 2.5B
Resolution 1920×1080
Frame Rate 30 fps
Memory Usage 8 GB FP8
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