zai-org/CogVideoGitHub
calls Phantom “Choose it when subject consistency from reference images matters more than broad text-to-video coverage.”
text and image to video generation: CogVideoX (2024) and CogVideo (ICLR 2023)
13.0kPythonslowing
Phantom-video/Phantom Alternatives
Phantom is queued for analysis. Crawling candidates and ranking them takes a few minutes. This page updates itself when the list exists — you can also come back later.
What is known so far comes from the other direction:
Listed as an alternative to
These projects were analysed and named Phantom among their alternatives. The relationship is not symmetric — how Phantom rates them is a separate judgement, made when Phantom is analysed in its own right.
Wan-Video/Wan2.2GitHub
calls Phantom “choose it when the task is subject-consistent generation across shots, narrower than general text-to-video.”
Wan: Open and Advanced Large-Scale Video Generative Models
17.4kPythonactive
Wan-Video/Wan2.1GitHub
calls Phantom “Choose it when you specifically need subject-consistent video generation; it's a specialized, older diffusion research model, not a general T2V/I2V suite.”
Wan: Open and Advanced Large-Scale Video Generative Models
16.9kPythonactive
Tencent-Hunyuan/HunyuanVideoGitHub
calls Phantom “only when you specifically need subject-consistent video from reference images; it is narrower than general T2V”
HunyuanVideo: A Systematic Framework For Large Video Generation Model
12.5kPythonactive
Lightricks/LTX-VideoGitHub
calls Phantom “narrower: video generation focused on subject consistency; useful for object-centric consistency rather than open text-to-video.”
Official repository for LTX-Video
11.0kPythonslowing