π What is Anima_LiquidMix?
Anima_Liquid is an experimental merge model designed to modify rendering tendencies while preserving Animaβs original prompt understanding as much as possible.
It was created by integrating custom-made LoRAs into multiple checkpoints in order to test how much texture, rendering characteristics, and visual behavior can be controlled through model merging.
Because the basic internal structure of Anima is preserved after merging, the model can also be used as a base checkpoint for LoRA training.
This makes it useful for purposes such as:
Testing LoRA behavior
Training experiments
Comparing rendering behavior between different merged checkpoints
𧬠Anima 2.9B / 40-Layer Version
As a new experimental branch, a version based on Anima 2.9B has been created, expanding the main DiT from the original 28 blocks to 40 blocks.
In this version, the existing Anima_LiquidMix weights were expanded into the 40-layer structure while attempting to preserve the original LiquidMix rendering characteristics as much as possible.
The 12 additional DiT blocks introduced in Anima 2.9B are placed at the following positions:
2, 5, 8, 11, 14, 17, 21, 24, 27, 30, 33, 36
This 2.9B checkpoint can also be used as a base model for future LoRA training.
π² Changes from Preview Base
Modified contrast behavior
Added more variation in color and lighting
Enhanced texture rendering
Modified glow and effect rendering
Changed rendering tendencies for fantasy / furry / creature-themed characters
Added experimental support for the 40-layer Anima 2.9B architecture
Improved support for newer character knowledge derived from Anima 2.9B
π§ͺ Purpose
This model was not created to reproduce any specific art style.
Instead, it is an experimental model intended to observe and test how model merging and LoRA integration affect rendering behavior.
The Anima 2.9B version also explores how rendering changes when a checkpoint originally developed around the 28-layer Anima architecture is expanded into a 40-layer DiT structure.
Because of this, generated results may vary significantly depending on:
Prompt
Sampler
Seed
LoRA
Checkpoint version
Other generation settings
π© Recommended Use
Comparing multiple Anima-based checkpoints
Comparing 28-layer and 40-layer Anima models
Testing Anima 2.9B merge behavior
Testing LoRA-integrated models
LoRA training experiments
Generating fantasy / furry / insect / monster characters
Testing glow, effects, and high-contrast rendering
Testing newer characters learned by Anima 2.9B-derived checkpoints
π¦ Recommended Settings
Sampler: ER SDE / Euler a / DPM++
Steps: 20β30
CFG: 4β6
Resolution: 1024β1536
The Anima 2.9B version may behave somewhat differently from the original 28-layer models.
Depending on the prompt and subject matter, adjusting the sampler or CFG may improve results.
π½ Requirements
For the text encoder, qwen_3_06b_base is recommended.
For the VAE, QwenimageVAE_liquid1127 is recommended for more stable rendering, color balance, and highlight reproduction.
When using the 40-layer Anima 2.9B version, your ComfyUI setup must also be capable of correctly detecting and loading the expanded 40-block DiT architecture.
In addition, older LoRAs made for the original 28-layer Anima architecture may not be fully compatible with the 40-layer model without modification.
For legacy 28-layer LoRAs, a compatibility LoRA loader can be used to remap the original block indices to their corresponding positions in the 40-layer model.
π Notes
This is not an official model
This is an experimental merge created for testing purposes
The Anima 2.9B version is also experimental
The 40-layer version has a different internal structure from the original 28-layer Anima models
Legacy LoRAs may behave differently on the 40-layer model
Unexpected outputs or unstable behavior may occur
Compatibility may vary depending on the ComfyUI version and model loader implementation
π₯ Feedback
Feedback and example generations are welcome.
In particular, comparison results between:
The original Anima_LiquidMix
The 40-layer Anima 2.9B version
Legacy 28-layer LoRAs used with the 40-layer version
would be especially helpful for further testing and development.



















