Nodes/ComfyUI MiniMax H3 Myang/沐阳 H3 · 采样器(内部·步级预览)
ComfyUI Node

沐阳 H3 · 采样器(内部·步级预览)

The sampler that shows you real frames at every step, not blurry mush

By civilcoco·Created about a month ago·Updated 20 days ago· 7
沐阳 H3 · 采样器(内部·步级预览)
  • noise
  • guider
  • sampler
  • sigmas
  • latent_image
  • vae
  • output
  • denoised_output
◄run_id►
◄owner_id►
◄segment_index1►
◄total_segments1►
◄pass_labelsample1►
◄reserve_vram_gb0.00►
◄preview_interval1►
◄preview_modevae►
◄return_denoisedfalse►

During a long video generation you're watching the preview for feedback, and ComfyUI's default preview - the latent-to-RGB blurry smear - tells you almost nothing until the very end. 沐阳 H3 · 采样器(内部·步级预览) (H3SamplerAdvanced) is the pack's internal sampler that replaces that: at every sampling step it VAE-decodes a real frame and pushes it to the frontend. You watch the actual picture form, which for multi-minute long-video runs is the difference between "looks broken, cancel it" and "wait, it's actually coming together."

Functionally it's a drop-in for SamplerCustomAdvanced - same shape, same job - so it fits anywhere that node does. It takes the noise, guider, sampler, sigmas, and latent_image, runs the sampling loop, and returns the finished LATENT. The extra inputs (run_id, owner_id, segment_index, total_segments, pass_label) are the progress bookkeeping: they tag which run, which segment, and which pass each preview belongs to, so the Director's panel can file frames correctly. pass_label defaults to sample1 and becomes sample2 on a second pass - which is how the panel distinguishes first-pass from refined previews.

The preview itself is a proper decode: it pulls one temporal token from the middle of the current latent, decodes it with the VAE, and saves a PNG to ComfyUI's temp directory. That's more expensive per step than the blurry default, so it's a genuine trade - but for a workflow where a single segment takes minutes, the cost is noise and the visibility is the point.

Inputs

  • noise / guider / sampler / sigmas / latent_image / vae - the standard advanced-sampler wiring.
  • run_id / owner_id / segment_index / total_segments - progress identity.
  • pass_label - which pass this sampling belongs to.

Output: output (LATENT), the sampled latents, exactly like the stock node.

Install and why you won't wire it

Pack install: ComfyUI Manager search "ComfyUI-MiniMaxH3-Myang", or git clone https://github.com/civilcoco/ComfyUI-MiniMaxH3-Myang into custom_nodes, restart. No extra Python deps.

Like the other 内部 nodes, the description says "请勿手动添加" - the Director and long-video expander place it for you. You'll meet it when you're curious why the previews are crisp, or when a custom graph needs the same step-level visibility. And the pack-wide reminder stands: H3's local weights are territory-restricted by community license (US/EU/UK/South Korea excluded), and after any ComfyUI update you should re-validate a two-segment run before trusting a long chain.

Category沐阳 H3

Inputs (15)

NameTypeDefaultDescription
noiseNOISE—
guiderGUIDER—
samplerSAMPLER—
sigmasSIGMAS—
latent_imageLATENT—
vaeVAE—
run_idSTRING—
owner_idSTRING—
segment_indexINT11–999—
total_segmentsINT11–999—
pass_labelSTRINGsample1—
reserve_vram_gbFLOAT0.000–8—
preview_intervalINT10–100—
preview_modeoptCOMBOvaelatent_rgb 不加载 VAE;vae 为旧版清晰预览
return_denoisedoptBOOLEANfalse仅实验性连续 Sigma 使用:返回分段点预测的干净 x0;普通采样关闭,避免额外复制 latent

Outputs (2)

NameTypeDescription
outputLATENT—
denoised_outputLATENT—