Z-Image Split-Sigma Workflow: ZiB to ZiT — v4.6

The short version is this:

• You can still use the workflow very simply by writing a normal prompt.

• You can open the Prompt / Prompt Builder subgraph and enable wildcard builder nodes if you want automated prompt variation.

• You can load an image into Prompt From Image if you want Gemma4 to enhance from an image.

• The Prompt Enhancer can improve either the basic text prompt or the image-guided prompt.

• The Image Saver now saves the seed used, as well as the other generation metadata.

What this workflow does

At its core, this workflow still combines Z-Image Base and Z-Image Turbo. Base handles the initial composition and structure, and Turbo is used to refine the result.

This workflow includes:

• Text-to-image generation

• Image-to-image

• Built-in ControlNets

• A new Prompt / Prompt Builder subgraph

• Sequential and random wildcard prompt tools

• Prompt enhancement using Gemma4

• Prompt enhancement from a loaded image

• Optional post-processing

• Optional upscaling with SeedVR2 and Ultimate SD Upscale

• CivitAI-friendly metadata saving

• Saved image data that includes checkpoints, LoRAs, prompt information, dimensions, sampler data, and now the seed used

Important first step: custom nodes required

There are more custom nodes in 4.6 than there were in the 4.0 workflow.

Some custom node packs still need to be installed through ComfyUI Manager or manually cloned into your ComfyUI/custom_nodes/ folder:

• rgthree-comfy: https://github.com/rgthree/rgthree-comfy

• ComfyUI-Image-Saver: https://github.com/alexopus/ComfyUI-Image-Saver

• ComfyUI-Impact-Pack: https://github.com/ltdrdata/ComfyUI-Impact-Pack

• ComfyUI-LG_SamplingUtils: https://github.com/LAOGOU-666/ComfyUI-LG_SamplingUtils

• ComfyUI_essentials: https://github.com/cubiq/ComfyUI_essentials

• ComfyUI-Easy-Use: https://github.com/yolain/ComfyUI-Easy-Use

• ComfyUI-KJNodes: https://github.com/kijai/ComfyUI-KJNodes

• RES4LYF: https://github.com/ClownsharkBatwing/RES4LYF

• ComfyUI ControlNet Aux: https://github.com/Fannovel16/comfyui_controlnet_aux

• ComfyUI-DepthAnythingV3: https://github.com/PozzettiAndrea/ComfyUI-DepthAnythingV3

• ComfyUI-SeedVR2_VideoUpscaler: https://github.com/numz/ComfyUI-SeedVR2_VideoUpscaler

• ComfyUI-Unload-Model: https://github.com/SeanScripts/ComfyUI-Unload-Model

• ComfyUI_UltimateSDUpscale: https://github.com/ssitu/ComfyUI_UltimateSDUpscale

• WAS Node Suite - Revised: https://github.com/ltdrdata/was-node-suite-comfyui

• comfyui-vrgamedevgirl: https://github.com/vrgamegirl19/comfyui-vrgamedevgirl

These custom nodes are included with the workflow package, so they should be inside the zip file and do not need a separate download:

• ComfyUI-SequentialWildcardPrompt

• ComfyUI-WildcardPromptAssembler

• ComfyUI-WildcardPromptToolkit

• mp_aspect_res_selector

Place the included custom node folders into:

ComfyUI/custom_nodes/

For a Windows portable install, that is usually:

ComfyUI_windows_portable/ComfyUI/custom_nodes/

After installing or copying the custom node folders, restart ComfyUI or refresh the node list.

Also, the Film Grain and Sharpen nodes in this workflow are provided by comfyui-vrgamedevgirl, so if those nodes are missing, that is the pack to check first.

Main workflow overview

The main workflow overview has changed slightly in 4.6. The big visible change is that the old prompt-related sections have been replaced by the new Prompt From Image loader, the new Prompt / Prompt Builder node, and the Gemma4 Prompt Enhancer node.

The workflow is still laid out so that the main controls are accessible from the front page:

• Image Saver

• ZiB LoRA Loader

• ZiT LoRA Loader

• Prompt From Image

• Prompt / Prompt Builder

• Prompt Enhancer

• Negative Prompt

• Image 2 Image

• Latent Switch

• Global

• LG Noise Injection

• Post Processing

• Optional upscaling sections

For normal use, you can start from the main workflow page. You do not need to dive into every subgraph straight away. I would strongly recommend running a simple text-to-image test first, then enabling the extra sections one at a time.

1. Global subgraph

The Global subgraph is still the heart of the workflow. This is where the main Z-Image Base and Z-Image Turbo models are loaded, and where the diffusion settings, aspect ratio, dimensions, seed handling, scheduler, VAE, and latent setup all come together.

In simple terms:

• ZiB / Base handles the first composition pass.

• ZiT / Turbo handles the refinement pass.

• The mp_aspect_res_selector node controls aspect ratio, orientation, megapixels, and aligned output dimensions.

• The seed generator now feeds the Image Saver properly, so the saved file records the seed that was actually used.

• The workflow is set up to create a strong base image, then push it through a refined second stage.

The aspect selector is still one of the most useful quality-of-life parts of the workflow. You can choose an aspect ratio, portrait or landscape orientation, a target megapixel value, and the node works out sensible dimensions for you.

By default, I usually work at around 2 megapixels for normal generation. That gives a good balance between quality and speed, and it leaves the optional upscaling paths available if you want to push the image further later.

The Global section also includes the VAE switch, tiled VAE decode, sampler, scheduler, split sigmas, sigma resampling, and cache/VRAM cleanup nodes. The default values are the ones that have worked best for me so far, but this is absolutely a place where people who like to tinker can experiment.

One small but important 4.6 change: image saving now includes the seed used. In older versions, the saved metadata was useful, but the seed handling was not as complete as I wanted. This version is much better for going back through older generations and understanding exactly how an image was made.

2. Prompt and negative prompt

The standard positive prompt flow is now handled through the Prompt / Prompt Builder section.

For simple use, just type your prompt into the main Prompt / Prompt Builder prompt field and run the workflow. You do not have to enable the wildcard builder nodes. If you want a normal, controlled prompt workflow, keep it simple and use it like a regular prompt box.

The negative prompt is still handled separately in the red Negative Prompt node. I have included a standard negative prompt note in the workflow as a starting point, but you should adjust it to suit your own style and subject matter.

3. Prompt / Prompt Builder subgraph

This is one of the biggest changes in 4.6.

The Prompt / Prompt Builder subgraph can be used in two ways:

• As a simple prompt box

• As a wildcard prompt builder

If you only want to write one prompt manually, you can ignore most of the inside of the subgraph, just make sure the 6 wildcard rule builder nodes are bypassed. Type the prompt in via the main graph, run the workflow, and carry on as normal.

If you want the workflow to build prompts for you, enter the subgraph and enable the Wildcard Rule Builder nodes you want to use. The included example is set up around character, outfit, pose, wings, framing, and camera angle style wildcard files, but the same system can be used for your own subjects, styles, locations, lighting, camera terms, character details, or anything else that works well as a line-by-line wildcard list.

The prompt builder is made from three main parts:

• Wildcard Rule Builder nodes

• Wildcard Config Combiner

• Wildcard Prompt Assembler

Wildcard Rule Builder nodes

Each Wildcard Rule Builder node controls one wildcard source.

The important fields are:

• token_name

• wildcard_file

• mode

• start_line_number

• repeat_each_line

token_name is the name of that wildcard rule. In the included setup, the example token names include prompt, outfit, pose, wings, framing, and camera_angle.

Write a base prompt, that uses the token_names, so as an example;

{girl} is wearing {outfit} in {location}

Where girl, outfit and location are all the token names you have assigned to your wildcards.

wildcard_file is the text file the node reads from. Each line in the selected file is treated as an available option.

mode controls how the wildcard moves across workflow executions. In the included workflow, some nodes are set to next, and others are set to randomize.

next is useful when you want to step through a wildcard file in order. For example, you might want to move through a base prompt list one line at a time.

randomize is useful when you want variety. For example, poses, framing, camera angles, lighting ideas, locations, or style details can work well when they are randomly selected.

start_line_number is the starting line in the wildcard file. It is 1-based, so line 1 means the first line in the file.

repeat_each_line controls how many executions the workflow stays on one line before changing. If this is set to 1, it can change every run. If it is set higher, the same line will be repeated for several generations before moving on.

The Rule Builder also has a rule_preview output. This is useful for checking what the rule is doing before you rely on it for a larger batch.

Wildcard Config Combiner

The Wildcard Config Combiner collects the enabled Rule Builder outputs into one combined wildcard configuration.

In this workflow, it has six rule inputs:

• rule_1

• rule_2

• rule_3

• rule_4

• rule_5

• rule_6

You do not need to use all six. If you only want one or two wildcard sources, enable only those. If you want a more complex prompt recipe, enable more of them.

Wildcard Prompt Assembler

The Wildcard Prompt Assembler is where the final prompt is assembled.

It takes the wildcard configuration from the combiner, combines it with the prompt text, resolves the selected wildcard values, and outputs the finished prompt.

The important outputs are:

• prompt_out

• preview_text

• selected_values

• resolved_token_count

prompt_out is the final prompt that leaves the Prompt / Prompt Builder subgraph.

preview_text is the one to watch while testing, because it shows the run counter, the original prompt, the resolved values, and the final prompt.

selected_values is useful if you want to see exactly which wildcard values were chosen.

resolved_token_count is useful for checking whether the assembler actually found and resolved wildcard tokens.

The assembler also includes a run_counter. This matters for sequential wildcard behaviour. If the counter is set to increment after generation, the sequential rules can move forward each run. If you reset or change the counter, the sequence position changes as well.

Example wildcard setup in this workflow

The included 4.6 example uses these wildcard sources:

• prompt from a baseline prompt wildcard file, set to next

• outfit from a lingerie wildcard file, set to next

• pose from a pose wildcard file, set to randomize

• wings from a succubus wings/horns/tail wildcard file, set to...

Checkpoint · Unknown