RDBT [Anima]
Finetuned + distilled model. Doesn't have a default style. I use it to stack style LoRAs.
See Update Log section for version info. See this page for LoRA version.
All cover images are "raw" output, 1024px, no editing/upscale etc. Metadata included.
Sharing merges using this model is not allowed. It has special trigger words. There is no false positive. Known model thieves: NukeA.I (closed-weight on tensorart)
Usage:
Settings:
CFG scale: 1~4. This model has been guidance distilled. You can disable CFG (CFG 1) and run the model 2x faster. Cover images are without CFG for demonstration.
Prompt
Specific style is required! This model does not provide a default style. You should always prompt specific style. Or use a style LoRA. Otherwise, you will get random/mixed style. This is a feature, not a bug. I use this model as a starting point to stack more style LoRA.
(v0.32+) There are some "roughly classified" trigger words, they are trained so they have effect, but they are not "specific style":
@anime sketch: Low complexity. Rough outlines.
@digital anime illustration: Typical "anime". Clear and fine outlines. General complexity.
@digital art: More complex lighting, textures than typical "anime".
@cinematic digital art: More lighting, postprocess effects, semi-realistic, etc.
Quality tags:
It's recommended to omit all the quality tags, or just keep the "masterpiece".
Quality tags have been reinforced during distillation. Thus they don't have noticeable effects. Same as negative tags. If you use cfg, there is no need to dump "score_1, blurry, worst quality, jpeg artifacts, extra arms,... x100 words" in your negative prompt. Those things have been distilled out.
Omitting those redundant tokens also allows LLM to better focus its attention on other words.
Update Logs
(5/18/2026): b1 v0.35:
No step distillation. Just guidance distilled.
I'm dropping step distillation. Anima official has their plan to do step distillation (aka, turbo, 4/8-step, or whatever). They have the money and recourse and full dataset. I don't. And my cheap step distillation is kind of sh*tty, tbh.
If you need higher stability or speed, you can stack the extracted cosmos dmd2 lora the anima-turbo, basically can achieve the same thing, probably even better. I prefer 0.2x cosmos dmd2 lora.
(5/12/2026): p3 v0.32.b:
Less step distillation (means higher diversity but less stability). 12 steps is still doable, 24 steps is recommended for complicated prompt.
Styles reinforcement learning. I did this in v0.29, but not in v0.32.
(5/10/2026): p3 v0.32:
No more green-ish, color shifting.
Trigger words have been reclassified to avoid model learning a unified style. See updated "Usage" section.
Old trigger words for backup (v0.29 and before):
"digital anime illustration": common 2d anime.
"digital art", 2d art but not anime, mostly digital art.
"anime sketch": simplified/unfinished anime drawing.
(4/27/2026): p3 v0.29: Distillation algorithm was almost completely rewritten.
Increased diversity. This also improved lighting range, styles and LoRA compatibility.
Better details. This version can squeeze every single pixel out of the VAE.
(4/23/2026) p3 v0.27: Improved stability, details.
(4/18/2026) p3 v0.25: It's based on anima p3.
Previous testing versions, see this page
Description
FAQ
Comments (14)
Looks great. Really good work well done 👍. Have a ever considered collaborating with @duongve13112002 to make a solid, stable and high quality Preview 2 checkpoint? As I love preview 1 but the natural language prompt adherence is better especially for more complex scenes and with multiple subjects on P2.
Any examples? I tested p2 and I think prompt adherence is the same as p1, afaik, they were still using tag based captions. And RDBT has better prompt adherence than p2, at cost of built-in styles.
the original p1 does have some stability issues, but it is a "pretrained" model, it should be unbiased and thus unstable. It's ideal for finetuning, but not ideal for users.
I think p2 is a finetuned model, which is difficult to finetune again. Some people said it takes longer to train LoRA on p2, that might be the prove.
@reakaakasky it's been a while since I used it but what is your opinion on NetaYume Lumina aa I think it's great I don't know how it compares to anima tho.
Lumina has way better aesthetics than Cosmos predict 2.
Cosmos predict 2 has better logical understanding.
How are you training these ? LCM ?
just cfg distillation
I see , thank you
Was just curious to try as well.
Tried LCM but it didn't turn out that well , it may need same dataset as original model was trained on.
Works quite well with https://civitai.com/models/2466415/cosmos-predict25-2b-base-distilled-extracted-dmd2-lora at 0.7 strength, 12 steps cfg 1, and https://github.com/pamparamm/ComfyUI-ppm for somewhat working negatives
(silly example prompt: "2girls, kissing (score_9, blushing, :-1.0)" )
very cool
Do you have an fp8 version of anima preview 2?
no, I gave up. it's slower in ComfyUI. fp8 needs torch.compile to inline kernels. Right now torch.compile is unusable, and will be unusable forever if they enforce their dynamic vram mode. On my hardware it's even slower 20% than bf16 +compile.
https://huggingface.co/Bedovyy/Anima-FP8/tree/main
Not mine, not tested, enabled hw fp8, but no calibration metadata.
@reakaakasky Yea, i'm rolling now with silveroxides int8 quant. Slightly faster than fp8 while having basically bf16 quality. 2.34s/it vs. 1.58s/it on my hardware fp16 preview2 vs int8 preview2, no torch compile. Seeds look fairly similar. Btw you were right about klein anime finetune in the making. Apparently chenkin is at it.
. https://huggingface.co/silveroxides/Anima-Quantized/tree/main
@deitychaser I don's see the chenkin klein finetune on their page, or did they just start?
@mc355168 Yea, its still in trainig in testing.
Man all of my lora floading here since your checkpoint is my favorite and use it to generate sample for them lol Still enjoying the checkpoint very much thankfull for it !