This is a deceptive title: it pretends to be an article about HunyuanVideo-I2V 14B (a model which does not exist; HunyuanVideo is a 13B model) running on a moderate consumer GPU, but the link is directly to a pay-to-generate hosted image/video generation service (which also claims that the model requires GPUs with at least 60GB aggregate VRAM to run locally in a frontend like ComfyUI contrary to the headline here—this also isn't true, I know, I’ve run it on a 16GB card.)

The OP also posted a comment here that purports to describe the HunyuanVideo model, but other than the name and attribution to Tencent, the easily verifiable facts reported in that comment (the 14B model size and the 1.3B lighter companion model size) are not true for HunyuanVideo, but are true of a different popular video model, WAN 2.1.

This link is about an API provided by a company named WaveSpeed.ai probably unrelated to Tencent.

Tencent HunyuanVideo-I2V GitHub is there:

https://github.com/Tencent/HunyuanVideo-I2V

Tencent says this about the GPU requirements:

* Minimum: The minimum GPU memory required is 60GB for 720p.

* Recommended: We recommend using a GPU with 80GB of memory for better generation quality.

HunyuanVideo-I2V is an open-source AI video generation model developed by Tencent, designed for image-to-video tasks. It offers two versions: a 14-billion-parameter professional model that excels in generating complex motions and simulating physical dynamics, and a 1.3-billion-parameter lite version optimized for consumer-grade GPUs, requiring only 8.2GB of VRAM, making it suitable for secondary development and academic research.

Built upon a causal 3D Variational Autoencoder (VAE) and Video Diffusion Transformer architecture, HunyuanVideo-I2V efficiently models spatiotemporal dependencies. In the authoritative VBench evaluation, the 14B version achieved a leading score of 86.22%, surpassing models like Sora, Luma, and Pika, and securing the top position. The model is available on Wavespeed AI, providing convenient access for developers.