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ComfyUI-CapitanZiT-Scheduler ((UPDATED))

Type

Workflows

Stats

87

0

Reviews

Published

Feb 3, 2026

Base Model

ZImageTurbo

Hash

AutoV2
0BE030E8CD

Feb 3rd, 2026 Update v1.1.0

v1.1.0 adds two optional components alongside the original CapitanZiT linear scheduler:

  • Smooth Cosine Scheduler
    Alternative sigma schedule using a cosine curve (1.0 → 0.0).
    More gradual start/end than linear, useful for smoother transitions and photorealistic subjects.
    Works with low or higher step counts.

  • Minimal Change Flow Sampler
    New sampler (not a scheduler).
    Limits how much the latent can change per step to prevent drift and instability.
    Adjustable max_change_per_step (default 0.70).
    Can be used with any sigma schedule (CapitanZiT, Cosine, or others).

Nothing about the original behavior changed — CapitanZiT linear sigma is still the same.

You can now mix:

  • CapitanZiT + Euler → fastest

  • CapitanZiT + Minimal Change Flow → speed + extra stability

  • Smooth Cosine + Minimal Change Flow → max smoothness

Details, math, and usage examples are in the GitHub.


Just released a tiny custom node/scheduler specifically for Z-Image-Turbo in ComfyUI: CapitanZiT.

Why it matters:
Z-Image-Turbo is distilled for 8-9 step speed, and its official pipeline uses a clean linear sigma schedule (1.0 → 0.0) with Euler for flow-matching. CapitanZiT replicates this exactly using torch.linspace(1.0, 0.0, steps + 1) – no extra curves, no mismatches.

Results:

  • Extremely stable velocity predictions and denoising

  • Seed variance <5% (vs 10-15% in some defaults)

  • Cleaner, sharper outputs with minimal artifacts in low steps

  • Full compatibility with Turbo's DMDR distillation (logit-normal noise + dynamic renoising)

Features at a glance:

  • Select "capitanZiT" directly in KSampler/KSampler Advanced scheduler dropdown (plug-and-play)

  • Standalone "CapitanZiT Linear Sigma" node for SIGMAS output (perfect for SamplerCustomAdvanced)

  • Default steps 9, tunable, works flawlessly with euler/euler_ancestral

  • ~50 lines, no dependencies, <100MB VRAM overhead

Tested on bf16 variant, RTX 3090 GPUs: sub-second inference at 8 steps, noticeably more consistent than unoptimized setups. Pairs great with AuraFlow shift (5-7) if you want extra noise crushing.

Repo: https://github.com/capitan01R/ComfyUI-CapitanZiT-Scheduler
(Super simple install: git clone into custom_nodes → restart)

or

Via ComfyUi manager "ComfyUI-CapitanZiT-Scheduler"

For better textures :

  • Euler_cfg_pp (sharper textures), Euler_ancestral_cfg_pp (smoother textures).

  • Res_2s with (eta 0.65-0.75)

  • Option to use ModelSamplingAuraFlow ( 3,5,7).

Also great news for anyone who trained their Lora's on ZiT, the good preview sample you saw during the training you are going to see using this Sigma/Scheduler

If you're running Z-Image-Turbo regularly, this is a drop-in upgrade for stability. Feedback welcome!