MiniMax H3 Dual-Sampling Workflow | Ref2VA + Turbo LoRA - v1.0 Showcase
MiniMax H3 makes consistent cinematic videos with synced audio - fast.
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 multiple reference images into short cinematic videos. You keep characters and products consistent across shots. Dual sampling balances detail and smooth motion. Native audio stays synchronized. A 4-step turbo LoRA speeds generation. The ready-made MiniMax H3 graph saves setup time.
Important nodes:
Key nodes in Comfyui MiniMax H3 High Quality Dual-Sampling workflow
MiniMaxH3ReferenceToVideo (#56)
Fuses text, image, and optional video or audio references into conditioning and an initial audiovisual latent for H3. Adjust prompt to define subjects, scene continuity, shot timing, and sound design, and set width, height, and length to target aspect and duration. Use multiple reference images to lock identity and wardrobe when continuity matters.
Lora Loader Stack (rgthree) (#118)
Applies the MiniMax H3 turbo 4-step LoRA on top of the base model to improve detail at short schedules. Tweak the LoRA strength if edges get too sharp or if the base model style is being overridden. Keep LoRA layering minimal when the references already carry strong texture.
MiniMaxH3MemoryEfficientSageAttentionPatch (#70)
Enables memory-efficient attention for the H3 UNet so you can run higher resolutions or longer clips on modest GPUs. Turn it on for 8 to 12 GB cards or when you see VRAM spikes. Disable only if you are benchmarking raw throughput on high-memory GPUs.
SplitSigmas (#99)
Splits the scheduler into complementary sigma bands that feed the two sampler passes. If your scene is stable but lacks bite, shift more weight to the high-sigma branch. If motion jitters or identities drift, favor the lower-sigma branch and keep the extended intermediate switch off.
SamplerCustomAdvanced (#108)
First-pass sampler that lays down structure, motion, and identity. Keep the guider consistent with your prompt and references so the second pass has a clean base. Use this pass to test seeds and framing quickly before committing to refinement.
SamplerCustomAdvanced (#103)
Refinement sampler that uses a higher sigma slice to enhance detail and fix edges. Works best after a solid first pass; avoid overdriving it when faces or logos begin to oversharpen. Pair it with latent upscaling only when you need extra texture headroom.
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Notes
MiniMax H3 Dual-Sampling Workflow | Ref2VA + Turbo LoRA - see RunComfy page for the latest node requirements.