Wan2.1-VAE-upscale2x

模型介绍

A decoder-only finetune of the Wan2.1 VAE, with 2x upscaling integrated directly into the decoder. The main purpose of this is to kill the dreaded wan speckles/polka dots/grain, but it's also convenient for highres fix workflows. The outputs of the 2x decoder are usually much better than what you would get by running the outputs of the original decoder through an image upscale model, and even better, it's effectively free, since the compute cost of decoding is virtually unchanged. If you don't want to use the extra resolution, a slight blur and downsample will give you an original resolution image with much higher quality than the original decoder can produce. In particular, this VAE improves skin details and hair very significantly. It is trained almost exclusively on real images, so it may struggle with anime/lineart and text. It would be possible to finetune on anime/lineart, but I'm not aware of a suitable dataset that's licensed correctly and not just full of scraped media with massive copyright violations. If you know of an appropriate datset for this that is sourced from cc-by materials or similar, let me know and I'd be happy to try training it. The first released version is trained on images only, and is compatible with both Wan and Qwen since they share the same latent space. A video version is planned, but video training is more complex than image training, so it will take some time.

主要特点

特点摘要待依据来源补齐，不凭模型名称推断能力。

局限与注意事项

暂无足够来源支持具体缺点结论。请重点验证实际任务表现、时延、数据政策、许可与版本生命周期。

来源报价与费用分析

同一模型在不同渠道、地区和配置下可能采用不同价格。下表独立保留各渠道报价，不将渠道价格视为厂商官方统一价格。

公开评测与运行配置

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

常见问题

资料来源与可追溯记录

许可证：apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。