Create controlled reference-image-to-video clips with MiniMax H3 Fun ControlNet, using depth, pose, and optional SolAttn branches.

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

Turn a reference image into a controlled video. Keep your subject's identity, outfit, and scene consistent. Guide motion with H3 Fun ControlNet. Choose single-control or depth-plus-pose branches. Use optional SolAttn for faster runs. Create clean walks, turns, waves, and full-body movement.

Important nodes:

Key nodes in the workflow

Apply H3 Fun ControlNet

This node adds a control stream to the current model. It receives control frames extracted from a control video and applies them during the selected sampling window.

Important settings:

• strength controls how strongly the model follows the control.

• start_percent controls when the control begins.

• end_percent controls when the control fades out.

• For single-control runs, start around 0.6 to 1.0.

• For chained controls, keep the combined strength near 1.0 or lower.

Ending control around 0.6 is often useful because it locks motion and structure early while allowing later steps to recover texture and realism.

MiniMaxH3ImageToVideo

This node builds image-to-video conditioning from a text prompt and optional first frame. Use it when a single first-frame reference is enough and you want the simpler Branch 1 workflow.

MiniMaxH3ReferenceToVideo

This node provides persistent reference-image conditioning. Use it when the output needs to preserve a character, outfit, face, style, or product identity across the whole video.

ref_image_size: match is faster. ref_image_size: max uses larger reference tokens and can improve identity, but costs more compute.

CFGGuider

This node makes negative conditioning effective. Branch 1 uses a basic guider, so negative text is not strongly applied there. Branches 2 and 3 use CFGGuider, making them better choices when you need to suppress artifacts, unwanted limbs, text, watermarks, or style drift.

Sigma shift

The sigma shift node adjusts the video and audio diffusion schedules before sampling. Keep it in the chain unless you are intentionally experimenting with H3’s schedule behavior.

SolAttnPatch

This optional node accelerates the reference branch through sparse attention. Leave morton off, keep conservative exact-block settings when quality matters, and compare output with a fixed seed before deciding whether the speedup is acceptable for your content.

BasicScheduler

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Notes

MiniMax H3 Fun Control in ComfyUI | Depth and Pose Video - see RunComfy page for the latest node requirements.