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Loki Automation vs SeedVR2

Loki Automation

filmworkz.com

SeedVR2

github.com

Side by side

FigureLoki AutomationSeedVR2
Price from$136.58/moFree
Free plan—Yes
Free trial——
Open source——
WebYes—
WindowsYesYes
macOS—Yes
Linux—Yes
APIYes—
Self-hosted—Yes
Plans published31
Spec score · AI Video Restoration Software7.7 (#16)8.1 (#9)
PurposeLoki automates restoration, enhancement, conversion and delivery workflows using Filmworkz DVO Tools.SeedVR2 is a one-step diffusion-transformer model for video restoration at any resolution.
SupportFilmworkz offers Juno for 24/7 support in any language and says support tickets can be raised with an active support contract.The repository invites questions by email at [email protected].

Plans

Loki Automation

  • Loki Render$149 a month
  • Loki Render$1,639 a year
  • Loki 2.0 — Full VersionPriced on request

Loki Automation pricing →

SeedVR2

  • SeedVR2Free

SeedVR2 pricing →

In their own words

Loki Automation

Loki Automation has no write-up on Specifiction yet; its figures are above.

Visit filmworkz.com

SeedVR2

SeedVR2 is an open-source model for restoring video at arbitrary resolutions, with a one-step diffusion-transformer approach that does not add a separate diffusion prior. Its official ComfyUI release can upscale both video and images and provides four nodes to control the pipeline. A standalone command-line interface supports batch and multi-GPU workflows. Inputs may be RGB or RGBA images and video; the documented model choices are 3B and 7B, with FP16, FP8, and quantized GGUF options. Model offloading, VAE tiling, and BlockSwap are available to manage memory during inference. The research describes adaptive window attention, which adjusts window size to output resolution, and adversarial post-training for high-resolution restoration. Standalone installation instructions cover Windows, macOS, and Linux, including Apple Silicon MPS support. Input height and width must be multiples of 32, and the demo crops resized inputs to meet that constraint. SeedVR2 is licensed under Apache 2.0, and released inference code and model weights are linked from the repository. The plan is free.

Visit github.com