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SPECIFICTION
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ProHawk Vision Workstation vs SeedVR2

ProHawk Vision Workstation

prohawk.ai

SeedVR2

github.com

Side by side

FigureProHawk Vision WorkstationSeedVR2
Price from—Free
Free plan—Yes
Free trialYes—
Open source——
WindowsYesYes
macOS—Yes
Linux—Yes
Self-hosted—Yes
Plans published21
Spec score · AI Video Restoration Software7.1 (#24)8.1 (#9)
PurposeRestores degraded video and images for forensic work, live viewing, and video analysis.SeedVR2 is a one-step diffusion-transformer model for video restoration at any resolution.
SecurityThe technical sheet specifies AES-256 encrypted hashing for file handling; the product page also describes username and password authentication for live camera and VMS streams.A release note says model loading was restricted to tensor-only deserialization to prevent code execution from malicious .pth files.
SupportThe datasheet lists sales and support by phone at +1-800-902-6972.The repository invites questions by email at [email protected].

Plans

ProHawk Vision Workstation

  • Perpetual licensePrice not published
  • Subscription licensePriced on request

ProHawk Vision Workstation pricing →

SeedVR2

  • SeedVR2Free

SeedVR2 pricing →

In their own words

ProHawk Vision Workstation

ProHawk Vision Workstation has no write-up on Specifiction yet; its figures are above.

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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