ComfyUI-MiniMax-H3-Turbo

ComfyUI-MiniMax-H3-Turbo

Run MiniMax-H3 — joint video + synchronized audio — in as few as 4 sampling steps instead of ~20, with the MiniMax-H3 Turbo LoRA.

Two nodes drop straight into the official H3 workflow (text-to-video and image-to-video):

node	what it does
MiniMax-H3 Turbo LoRA	MODEL → MODEL, applies the turbo LoRA
MiniMax-H3 Turbo Sampler	→ SAMPLER, feeds SamplerCustomAdvanced

Which checkpoint — v4 (600) or v1 (850)?

For most work, use minimax_h3_turbo_v4_step600_ema.safetensors (from the LoRA repo). It's the strongest checkpoint so far: much better static / small-motion shots, markedly better micro-detail (faces, fingers, texture), and the over-sharpening / plastic look of the earlier v1 (~850) line is fully resolved.

v4 introduced a static-frame enhancement. The one trade-off shows up only at 4 steps with large, fast motion, where v4 can produce motion-smear / trailing ghosting (actively being fixed). Using 6–8 steps largely removes it — and v4 tolerates higher step counts better than v1 (which over-sharpens at high steps + strength 1.0). For the narrow case of 4 steps and heavy motion, the older v1 ~850 checkpoint can still be friendlier.

Using 6–8 steps?        ── yes ──►  v4-600  (recommended)
   │ no (4 steps)
   ▼
Heavy / fast motion?    ── no  ──►  v4-600  (recommended)
   │ yes
   ▼
                                    v1-850  (friendlier at 4-step heavy motion)

Still a preview — the two areas still being improved are audio and fast, intense motion.

Install

Via ComfyUI-Manager — search "MiniMax-H3 Turbo" and install. Or manually:

cd ComfyUI/custom_nodes
git clone https://github.com/larryvrh/ComfyUI-MiniMax-H3-Turbo

Then restart ComfyUI. Keep the node updated (Manager, or git pull) — it evolves alongside the weights.

Put the LoRA .safetensors into ComfyUI/models/loras/. You also need the base MiniMax-H3 model, VAEs and text encoder from the official release — see the MiniMax-H3 tutorial.

Use

Start from the official MiniMax-H3 workflow (t2v or i2v) and make two changes:

1. Insert MiniMax-H3 Turbo LoRA between the model loader and the sampler (… → Load Diffusion Model → MiniMax-H3 Turbo LoRA → SamplerCustomAdvanced), and pick the turbo .safetensors.
2. Feed SamplerCustomAdvanced from MiniMax-H3 Turbo Sampler, and set the scheduler node (BasicScheduler) to simple at ≥ 4 steps.

Everything else — conditioning, VAE decode, audio output — stays as in the official graph, so both t2v and i2v work unchanged. A ready-made t2v workflow is in example_workflows/ — drag it into ComfyUI to see the wiring.

Steps and strength

• 4 steps is the recommended minimum; 4–8 is the useful range. 6–8 steps look noticeably better than 4, so add steps if you can afford them. Past 8 steps it stops helping and can start to introduce over-sharp artifacts — no benefit to going higher, so stay in 4–8.
• Keep strength at 1.0. It's tuned for 1.0 and holds up across the 4–8 step range. Only reach for the dial if a specific clip misbehaves: blurry ghosting / smear → nudge up (~1.05–1.2), over-sharp grain → nudge down (~0.8–0.95).
• Keep the scheduler on simple.

Base model & low_vram

Base model — works with any MiniMax-H3 base: full (bf16, int8_convrot) and the pruned/curve variants (pruned_int8, pruned_fp8). The node detects a pruned base automatically and re-injects the LoRA's time-conditioning at run time (a small silu(t_emb) grid ships with the node for this), so **one LoRA file covers