Pixop vs SeedVR2
Pixop
pixop.comSeedVR2
github.comSide by side
| Figure | Pixop | SeedVR2 |
|---|---|---|
| Price from | $0.02/mo | Free |
| Free plan | Yes | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| API | Yes | — |
| Self-hosted | Yes | Yes |
| Plans published | 9 | 1 |
| Spec score · AI Video Restoration Software | 8.9 (#2) | 8.1 (#9) |
| Spec score · AI Video Upscalers | 9.0 (#4) | 8.3 (#11) |
| Integration | Pixop documents a Mimir integration that can submit videos, trigger processing jobs, and return job status updates and comments. | The maintainers state that a ComfyUI integration was released in November 2025. |
| Purpose | Pixop provides machine-learning video enhancement for broadcasters, streamers, and media companies. | SeedVR2 is a one-step diffusion-transformer model for video restoration at any resolution. |
| Security | Pixop says video is encrypted in transit and at rest, stored in encrypted Amazon S3, and processed and stored in AWS Ireland. | A release note says model loading was restricted to tensor-only deserialization to prevent code execution from malicious .pth files. |
| Support | Pixop’s documentation directs users who need help to contact its support email. | The repository invites questions by email at [email protected]. |
Plans
Pixop
- AWS Marketplace Pixop creditFree
- Storage$0.02 a month
- Pixop Super Resolution$0.08, paid once
- Download$0.09, paid once
- Pixop Denoiser$0.41, paid once
- Pixop Deep Restoration 2$0.49, paid once
- Pixop FILE direct billingPriced on request
- Pixop FILE via AWS MarketplacePriced on request
- Pixop PrimePriced on request
In their own words
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.