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SeedVR2 Long Video Upscaler — HD → 4K

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SeedVR2 Long Video Upscaler — HD → 4K

This workflow turns ComfyUI’s native SeedVR2 video upscale into an automatic long-video pipeline.

Instead of loading an entire video into GPU memory or manually processing one short segment at a time, VideoHelperSuite Meta Batch advances through the source automatically until EOF. A custom overlap helper carries boundary frames into the next batch so they are regenerated with future-frame context and written only once.

The result is a workflow designed for arbitrarily long videos, where memory usage depends on the chunk size, not the overall runtime of the source clip.

Highlights

  • Arbitrarily long source videos from a VRAM perspective

  • Automatic SeedVR2-friendly 4n+1 batch sizing from a simple chunk_seconds control

  • 8-frame contextual overlap by default

  • No duplicate frames at chunk boundaries

  • 2x upscale default: 1080p → 2160p / 4K UHD

  • H.264 yuv420p10le, CRF 12 default output

  • Original audio restored after processing

  • No second video encode during final audio remux

  • Optional inner latent splitting for additional VRAM savings

  • Optional ProRes output for editing/intermediate use

Default settings

  • Chunk duration: 2.0 s

  • Outer overlap: 8 frames

  • Scale: 2x

  • Split latent: off

  • Color correction: LAB

  • Codec: H.264

  • Pixel format: yuv420p10le

  • CRF: 12

  • Final container: MKV

Requirements

  • Current ComfyUI with native SeedVR2 support

  • ComfyUI-VideoHelperSuite

  • FFmpeg

  • SeedVR2 model files:

    • seedvr2_3b_int8_convrot.safetensors

    • seedvr2_ema_vae_fp16.safetensors

Installation

Clone the custom node directly from GitHub into your ComfyUI/custom_nodes folder:

cd ComfyUI/custom_nodes
git clone https://github.com/biogoly/ComfyUI-SeedVR2-LongVideo.git

Then restart ComfyUI.

After restart, load the included workflow:

ComfyUI-SeedVR2-LongVideo/workflows/SeedVR2_LongVideo_Upscale_v1.4.json

Repo here:

https://github.com/biogoly/ComfyUI-SeedVR2-LongVideo

OOM tuning

If you run out of VRAM:

  1. Lower chunk_seconds first

  2. If needed, enable split_latent as the secondary memory-control option

This workflow is meant to avoid duration-driven OOM by processing the video in streamed chunks instead of one massive pass.

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