⚡ Anima Workflow:

🛠️ Purpose & Design Philosophy

This workflow is designed for quality and autonomy, not speed. It follows an "all-in-one" philosophy: configure your settings, hit queue, and let the workflow handle everything from initial generation to high-res detailing in a single pass.

Not for Speed: If you want rapid-fire generations, this is not the tool for you. A solid, much faster alternative created by darksidewalker can be found here.
Personal Use: This was built for my personal production needs. It is not intended to be a "one-size-fits-all" solution, but I am sharing it for those who value the same high-fidelity results. Please adjust the settings to your preferences!
Heavy Duty: Due to the multi-stage processing, this workflow can be resource-intensive. In my experience, the detailers are not usually needed. YMMV.
On v1g and after: If the results are too blurry for you after USDU, you can try using the RTX nodes after it to help.
v2 is compatible with AIO versions of Anima models. Note: You might have to select a random model in the Checkpoint Loader node even if you are not using it. This is because it references your models/checkpoints folder. The opposite may also be the case if you are using the Checkpoint Loader node but not the Model Loader in the Diffusion Model Loader group which references the models/diffusion_models folder.

🚀 Key Features

Beyond standard generation and upscaling, this workflow integrates:

Power LoRA Loader: Efficiently manage multiple LoRAs without spaghetti wires.
Global Controls: Centralized Seed, Sampler, and Scheduler nodes for a unified experience.
Bypass Control to toggle features on/off.
Visual Validation: Integrated Image Comparer nodes to see exactly how your image evolves at every stage.
Upscaling: 2-stage upscaling using standard image upscaling and Ultimate SD Upscale (optional).
Triple Detailer Groups: 3-stage detailing using standard BBOX and SEGM detection models for faces, hands, and clothes.
CivitAI Ready: Images are saved with full metadata (Model, LoRAs, Prompts) for easy site parsing.

⚠️ Disclaimer & Compatibility

Install at Your Own Risk: Updating ComfyUI or adding custom nodes can break your environment. I am not responsible for any installation issues.
Portable Version: This was built and tested on the ComfyUI Portable version. Desktop app users may require additional troubleshooting.
"Your Mileage May Vary": Your environment is almost certainly different from mine. I do not guarantee 1:1 compatibility.
Nodes 2.0: I strongly recommend disabling Nodes 2.0. It causes unpredictable behavior; I will not provide support for any issues arising from its use.

🤝 Support & Boundaries

No DMs: Direct messages are disabled due to high volume. Please use the Discussions tab below. Check previous comments first (unless there aren't any yet), as most common questions may have already been answered.
Custom Requests: I do not take private requests for custom workflows. If you need a specific solution built, please post a Bounty on CivitAI. There are many talented creators here who will be happy to assist you for a fee.
Modifications: You are free to add or remove nodes as you see fit. However, if you change the internal logic, you are responsible for your own troubleshooting.
The only place I am actively maintaining this workflow is here on civitai. If my workflows are being posted and monetized elsewhere, whoever posted them is obligated to provide support.

Description

This update removes the following:

CFGZeroStar

For Anima, this seems to do more harm than good leading to muddy or over sharpened details. Anima performs better without it for me.

JPS Custom Nodes for ComfyUI

This custom node pack is no longer needed since I have also removed the Global Sampler node.
The workflow is compact enough that the Global Sampler node is not needed. It shares the same custom node pack as the Global Seed node, so if you really need the Global Sampler node, you can just re-add it easily.
Part of the math for upscaling in the subgraph used a node from JPS and has been replaced with nodes from ComfyMath.

Removed the SD3 Latent node

This was interesting to try, but I prefer stability.
I also replaced the JPS node that was used for picking the latent size with the SDXL Empty Latent image node from rgthree-comfy.
Now you can use that node for preset sizes and the normal Empty Latent node for custom sizes.

Notable mention:

I tested out CLIP NegPip from ComfyUI-ppm and it works pretty well, but decided against adding it to the workflow at this time.

It lets you use negative values in the positive prompt and definitely makes a difference compared to not having it.
This can be useful if you are finding that your negative prompt is having little to no impact.

Generation time:

Using 40 steps, CFG 1.6, Euler A CFG++/Euler A CFG++ with Simple/Beta/Beta57 and Upscaling 2x into USDU with 20 steps, CFG 1.6, Denoise 0.20 to 0.22, and Euler A CFG++/Euler A CFG++ with Beta takes me from between 150 to 160 seconds per run on a 5060ti 16GB.