daVinci-MagiHuman Workflow in ComfyUI | Audio-Video Human Synthesis - v1.0 Showcase

Creates lifelike avatars with synced speech and expressive motion.

Who it's for: creators who want this pipeline in ComfyUI without assembling nodes from scratch. Not for: one-click results with zero tuning - you still choose inputs, prompts, and settings.

Open preloaded workflow on RunComfy

Open preloaded workflow on RunComfy (browser)

Why RunComfy first
- Fewer missing-node surprises - run the graph in a managed environment before you mirror it locally.
- Quick GPU tryout - useful if your local VRAM or install time is the bottleneck.
- Matches the published JSON - the zip follows the same runnable workflow you can open on RunComfy.

When downloading for local ComfyUI makes sense - you want full control over models on disk, batch scripting, or offline runs.

How to use (local ComfyUI)
1. Load inputs (images/video/audio) in the marked loader nodes.
2. Set prompts, resolution, and seeds; start with a short test run.
3. Export from the Save / Write nodes shown in the graph.

Expectations - First run may pull large weights; cloud runs may require a free RunComfy account.

Overview

Bring your characters to life with the MagiHuman workflow. It lets you generate natural talking humans with perfect lip-sync, expressive faces, and realistic motion. Use text, audio, or prompts to create studio-quality avatars for videos, presentations, and storytelling. Designed for speed and accuracy, it delivers consistent performance even at real-time rates. Ideal for content creators, designers, and developers seeking humanized digital outputs with coherent body movement and multilingual support.

Important nodes:

Key nodes in ComfyUI daVinci-MagiHuman workflow

• MagiHuman_LATENTS (#13)
  Builds the joint latent canvas for video and optional audio, taking the reference image and clip length. Adjust seconds to set duration and ensure your reference image is well framed for the motion you describe. Higher base resolution helps facial fidelity but also increases VRAM and decode time.

• MagiHuman_SM_ENCODER (#95)
  Encodes the Video Prompt into positive and negative conditioning for the sampler. Put the exact spoken line in quotes and name the language to improve lip closure and timing. Use the negative field to suppress artifacts like “subtitles,” “static,” or “room echo.”

• MagiHuman_SM_KSampler (#9)
  Runs daVinci‑MagiHuman denoising to co‑generate video and speech latents. The seed controls reproducibility, while steps and the internal schedule trade speed for detail and motion stability. For variation without losing identity, change seed or lightly rephrase the performance portion of your prompt.

• MagiHuman_EN_DECO_VIDEO (#5)
  Decodes video latents with the Wan 2.2 VAE into RGB frames for export or upscaling. Use this path for the fastest end‑to‑end render; long clips or higher resolutions will linearly increase decode time.

• MagiHuman_DECO_AUDIO (#6)
  Decodes audio latents to waveform and sends them through loudness normalization for even playback. If you later switch to audio‑driven generation, route your external audio into the latent builder and keep this decode path for final muxing.

• RTXVideoSuperResolution (#93)
  Optional post‑upscaler that sharpens edges and reduces ringing. Use moderate strength to improve clarity without introducing temporal shimmer.

Notes

daVinci-MagiHuman Workflow in ComfyUI | Audio-Video Human Synthesis - see RunComfy page for the latest node requirements.