CHAMELAION LipSync API vs Hallo

CHAMELAION LipSync API takes video and audio input and produces a video with lip movements matched to the audio. It accepts MP4 video and WAV or MP3 audio by public URL or direct upload. Active-speaker detection runs automatically but can be disabled for an individual request. The maker says the model retains speaker identity, speaking style, and expressions while adapting mouth movements to new audio. Listed uses include dubbing and translation, AI avatars, creative ads, and dialogue replacement or personalization. SDKs are listed for Python 3.8+ and TypeScript/Node.js 18+. Requests require a Bearer token or x-api-key header, except at the health endpoint; generation endpoints are limited to 60 requests per minute, and concurrent job limits depend on the plan. Starter is free and includes 24,000 tokens and two minutes of translation and lip sync, with a watermark. Basic costs €4.00 per year and lists 60,000 tokens and five minutes. The maker says its servers are in Europe and users retain ownership of generated videos. Profile views may work when the mouth remains visible; extreme close-ups, side views above 90 degrees, and cropped mouths are difficult cases.

Hallo generates an animated portrait video from a still image and driving speech audio. Its hierarchical audio-driven synthesis is designed to align lip, facial-expression, and pose movement with the audio, while separate inference weights let you adjust those three motion areas. The source image should be square, show a forward-facing face occupying 50%–70% of the frame, and have less than 30 degrees of rotation. Driving audio must be a clear-vocal English WAV file; background music is allowed. Inference saves an MP4 to `.cache/output.mp4` by default, with another output path available. Listed requirements are Ubuntu 20.04 or 22.04 and CUDA 12.1, with an A100 named as the tested GPU. Pretrained checkpoints and supporting models are available through Hugging Face. The project lists Linux, Windows, and self-hosted platforms, with community resources for Windows, ComfyUI, a WebUI, Docker, and RunPod. Its repository includes preprocessing and training code for multi-node and multi-GPU work. Hallo is free, open source under MIT, and its training data is English, so driving audio is limited to English.