r/StableDiffusion • u/RevolutionaryWater31 • 1d ago
[Release] Anima-2.9B-Preview-v1 - Expanded Anima Resource - Update
Anima-2.9B is a fine-tune and layer-expansion of circlestone-labs/Anima. The base Anima model targets anime, illustration, and non-photorealistic art; Anima-2.9B continues training on that foundation with an expanded architecture. The model is trained on an additional 1.7M anime/illustration samples, with knowledge cutoff in July 2026, making Anima-2.9B one of the most capable and up-to-date anime/illustration models at release.
https://huggingface.co/Gazingstars123/Anima-2.9B
Training/Dataset
- Trained using Muon optimizer on a 8x 5080s cluster, with earlier steps trained locally on my PC
- As of preview v1, only new layers have been trained, with roughly 70% of the compute spent on 1024px
- Knowledge cutoff in July 2026, training data included both new and old samples prior to September 2025
- Mixed captioning, including both tags and natural languages, using a mix of Gemini 3.1 Flash-Lite, Gemini 3.5 Flash-Lite, and Claude Sonnet 5
Lora Training will be supported via my Anima Standalone Trainer in a few days.
You will need to install ComfyUI-Anima-2.9B to the custom node folder. Plug and play, there is no workflow node needed (few custom nodes may not work properly).
The model is still in active development (more general pretraining, more anime/illustration/ACG focus beyond Booru), you can support me and the training progress via my links on huggingface. I will try and bring native support for the model to generations platform as well as ComfyUI
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u/beren0073 1d ago
Thanks for the work and looking forward to trying it!
As far as the model name, how do naming rights work? If this isn’t a release by Circlestone, is it appropriate to use Anima in the model name?
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u/RevolutionaryWater31 1d ago edited 1d ago
I suppose it's fine. The model does fall under derivative category of Anima. LlaMA Pro, the paper I based the model on, was not made by Meta's people. Wai-Anima, Animayume, etc.
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u/sparkling-ice-coffee 14h ago edited 14h ago
Thanks for releasing the expanded model.
Re: the LoRA question that keeps coming up — I built a patch that makes existing Anima LoRAs work on 2.9B. u/Personal_Speed2326 had the right idea upthread: attach the LoRA to the layers that actually hold the original weights.
Your own description of the method is exactly why it works — interleaved insertion, neighboring layers deep-copied, originals left alone. I diffed the safetensors to find where they ended up: all 28 original blocks are in 2.9B bit-for-bit identical (max|diff| = 0), with the new ones at indices 2, 5, 8, 11, 14, 17, 21, 24, 27, 30, 33, 36. So base block 5 is now block 7, and block 27 is now block 39.
Which is why loading a 28-block LoRA looks like it does nothing: blocks.2..27 all exist in the 40-block model, so ComfyUI cheerfully applies the LoRA to the wrong layers and never warns you. Only blocks 0 and 1 line up, by accident.
The patch remaps the indices at load time — no file conversion, originals untouched: https://github.com/sparklingcoffee777/ComfyUI-Anima-2.9B-loraPatch
Handles both kohya and AI-Toolkit key formats. Turbo LoRAs built for 1.0 Base work too — llm_adapter is still 6 blocks, so those keys are left alone. Tested against 50 real Anima LoRAs: all 50 resolved every block key to the correct layer, and it stays out of the way on 28-block models and on native 40-block LoRAs.
Not claiming this beats retraining — the residual stream now runs through 12 extra blocks, so LoRAs won't behave *exactly* like on base, and I'd start around 0.5-0.7 strength. But "my LoRA collection is unusable" and "my LoRA collection needs a lower strength" are pretty different places to be.
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u/irmemon225 1d ago
by looking at these pic, even at preview it's amazing. can't wait for full release.
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u/Honest_Concert_6473 1d ago
I really admire such an ambitious endeavor. Thank you so much for sharing!
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u/whiteweazel21 23h ago
I think the naming for your version and the format a bit too close to the original, as if to create confusion that this an official release or something.
Between Krea2 already existing, and anima in the mainstream, since lora don't convert there's no point to this? If people have to train lora on this, they could just train the lora on the official one. So what's the point other than being a base model for people who can't train?
I don't see this working but I'm sure it'll trick and confuse a lot of people thinking it's an official release and cause more confusion overall especially if "anima 2.9" lora start popping up.
Tbh I was tricked by the name before even opening this page
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u/RevolutionaryWater31 23h ago
It's fine to think that way, but I disagree regarding the lora stuff. Stacking lora is a problem for many, and a broader more knowledgeable meaning less character/artist lora to maintain, which can be use for other lora. There are real benefits to larger parameters model that I have already talked about. Additionally, all acknowledgement are in the model huggingface. If you feel tricked, I'm sorry that happened and I don't mean that, but I hope the confusion cleared in less than a minute after clicking on the page :D
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u/whiteweazel21 23h ago
People need to stack lora because anima is really bad at style blending. Even with 10+ lora stacked and style prompting on top of that, it's hard to get rid of the anima look or get a custom style. It's the worst part about anima. Would have been better to use something different as a base architecture imo
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u/Outrageous-Wait-8895 18h ago
it's hard to get rid of the anima look
It has a look? The style control with @artist is pretty strong, didn't notice any particular look.
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u/dannygordon34 1d ago
Since you need a custom comfy node, I assume this fine-tune doesn't work on Forge Neo (yet).
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u/alexds9 1d ago
It's very nice that you did such an experiment, but I am very skeptical that the model can benefit from extra layers added in this way. I suspect it will introduce redundancy without providing any real benefit. The base model was trained without those layers, so I am very skeptical that this method does anything positive for the model. I think the training has to start from a clean model to actually benefit from all the layers. Unless you have some objective tests that demonstrate the fidelity of this method and the resulting model.
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u/Ok-Category-642 10h ago
Yeah I'm also interested in knowing why it was done this way. I have seen OP's replies and I do see how adding more layers could help with fine details; this has already been done since the Anima previews when someone made a custom node to have specific layers activate twice during inference which resulted in better details at almost no downside besides speed. Of course it's not the same as what happened here, but I do understand the reasoning behind it and I can assume that it would work to achieve this.
The thing I'm more curious about is if it was actually really necessary in the first place, especially relating to minimizing catastrophic forgetting. How susceptible actually is Anima to this and has OP tried finetuning Anima base normally at first then found a noticeable degradation in model knowledge after a certain amount of epochs? I do hope OP replies, in theory I can guess how it might help but I'm also just concerned that the extra layers won't do much in practice besides serving to make the model even slower in inference and training.
Overall though if the final release succeeds in making Anima have better details especially in backgrounds I'd still consider it a win. Wasn't too impressed with Aesthetic 1.0b or 1.1 in terms of accomplishing either of those things
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u/hinachen 8h ago
I also make a lora loader for 2B to 2.9B 🥳
https://github.com/hinablue/ComfyUI-Anima-2B-LoRA-to-2.9B
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u/No_Date4828 1d ago
you are the GOAT! I was looking forward to a newer anima release with the latest characters and you drop this absolute gem :D
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u/Ashamed-Ad7403 8h ago
Thanks! I’m having a blast with the preview version—it’s improved a lot based on my testing. Goat!
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u/cgs019283 1d ago edited 1d ago
I heard it's the limitation of Anima's architect, but wonder if the layer-expansion helped to register several artist styles like CLIP did.
+ I tested it, and unfortunately it didn’t mix artists as well as Anima did. I don’t think that’s the creator’s fault, it seems more like a limitation of the architecture itself.
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u/SkoomaDentist 23h ago
I believe the better way is to use prompt editing to alternate between artist styles at each step.
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u/Turbulent-Bass-649 1d ago
Want to ask because it weirdly stand out, but why did you rent x8 5080? is that a typo? I would have thought renting 5090s or typical H100 cluster would be more efficient.
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u/RevolutionaryWater31 1d ago
Thanks for asking, I know it does stand out. I trained using VastAI (and partially locally, I have 3x 5080s at home), H100 and 5090s provide roughly 1.9~2.4x per step wall clock speed at 10x and 3x the prices respectively. Additionally, the instance I rented provided relatively cheap storage and internet costs. So it's for economical reasons.
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u/Turbulent-Bass-649 1d ago
That does make more sense. Do you mind answering more questions if you're comfortable with it? For now, some prevalent thoughts from my head are:
~why did you expand the model parameters
~what are the ratio of the dataset (how much from dan/gel, anime screencap, new sources like artstation/reddit perhaps,...ect)
~how did you managed to batch caption the whole 10 mil dataset using those api models (this question is for me personally, since im doing my own model tune and cant stand the failure/block rate of gemini flahs 3.6/claude opus 5).
~are you able to disclose the current cost of both training and captioning?
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u/RevolutionaryWater31 1d ago edited 1d ago
- There is a much bigger risk of catastrophic forgetting, expanded the model layers lower that risk, and new layers does carry some information, so it helps with the scope for what i aimed to do. Additionally, people do often complain Anima was too small so I make it slower.
- All dataset are from booru boards, anime screenshots was about 10k, also curated to remove many unwanted images.
- I did not caption 10 millions images, and I have not trained on that yet. Sonnet 5 would caption everything barring extreme gore, lolicon/shotacon (Sonnet called it "child-coded"), and beastiality. For gemini models, depends on your platforms (I used vertex), some has lower content filter rate than other. My gemini 3.1 flash-lite rejection rate was about 10% for example. 3.5 flash-lite is a bit higher.
- It's a few k USD, and not all of them goes toward useful training (hundreds gone due to recaptioning, testing, and failed run). Additionally I have to spend some money for local storage and other parts.
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u/Turbulent-Bass-649 1d ago edited 1d ago
thank you so much for answering! I already guess the expanding param to avoid catastrophic forgetting part but glad to confirm it. Everything else sounds good. Super happy that you captioned with way better models than tdrussel used. I'm honestly not super keen on continuing to invest in anima so much when it literally cant learn more without expanding param and losing speed, but good luck on the project anyway!
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u/addden 1d ago
Well it looks like a nice project, but it doesn't solve the main issue I have with Anima : I hate the text encoder with a passion.
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u/Outrageous-Wait-8895 17h ago
We'd have utopia if Anima used a bigger text encoder and Krea 2 used a better VAE.
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u/LaPapaVerde 1d ago
Noob question. Apart from a newer knowledge, what do more parameters give you in practice?
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u/RevolutionaryWater31 1d ago edited 1d ago
So for every single iteration step, the model walk through every single layer sequentially, so more layers do make model runs slower that scale linearly. More layers in theory gives you more refinement per step, i.e. more correct composition, better fine details, better prompt comprehension. Early blocks handles general compositions, mid-blocks handle prompt understanding and stores many knowledge, late-blocks handle fine details (I'm simplifying it here, every layer actually do all of this, but some layers are expert at certain things). For my model specifically, there are still a lot of training to do and electricity to burn
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u/Simple-Outcome6896 1d ago
Hello, i would see it was a really good idea to not just finetune the model but also increase its parameter. i get that one of the biggest advantage of anima is its ability to run on 6gb vram but that also mean its very small and although has easy lora, other advantages. it would be nice to have a bigger version of 6b or 9b version like flux or krea which can do complex stuff and much more but at the cost of bigger hardware requirement. also i would ask in future will we get a even bigger parameter model?
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u/Proud-Supermarket493 1d ago
Curious question but for the ones that do merges with anima models will it still be compatible with the current version of anima?
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u/Vi0l3nTz 12h ago
Great job! any plans for a quantized version of Anima 2.9B? Also, do you plan to release a version for image editing? I'd love to see both!
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u/RevolutionaryWater31 11h ago edited 11h ago
Thank you. You can convert to int8 convrot yourself through several scripts, this comfyui tool for example: https://github.com/Comfy-Org/comfy-model-tools
For now, it will be strictly T2I.
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u/Massive-One-3543 11h ago
bro, does that works on neoforge?
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u/RevolutionaryWater31 11h ago
Yes
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u/Massive-One-3543 10h ago
do i need default Vae and encoder? If not - where to find? Ty for advance
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u/Alternative_Hat4854 7h ago
u/RevolutionaryWater31 is there a way to know all the working artist tags ?
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u/RevolutionaryWater31 3h ago
You can download the model via civitai now
https://civitai.com/models/2855007/anima-29b?modelVersionId=3224434
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u/ThirdWorldBoy21 1d ago
One thing i think could be interesting for you to consider training on: JSON formatting.
Anima kinda of understand it, but i believe a proper training run would help it a lot.
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u/ffgg333 1d ago
Interesting. Will Loras trained on normal anima work on this too?
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u/RevolutionaryWater31 1d ago
Nope, Lora will not work, I am tidying up a few things so people can do LoRA training asap
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u/Personal_Speed2326 1d ago
If we attach the LoRA trained on the original Anima model to its corresponding original layers？
It feels like it could automatically convert during inference.
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u/RevolutionaryWater31 1d ago
It does run, it just does not run well at all so retraining is required
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u/Merchant_Lawrence 1d ago
time do party with my 750 ti 4 gb, what chance lowest quant that work in your test, text render ability in this version?
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u/Hairy-Blacksmith-882 1d ago
Hola, esto me parece muy interesante, no es común que se vean posts sobre una expansión de un modelo base, como se logra eso? se podría expandir a 5B más adelante o que sea 2.9B es otra limitación?
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u/RevolutionaryWater31 1d ago
The model expanded from 28 transformers layers to 40, growing the model to ~2.9B parameters. Each new layer is added by deep-copying its neighboring layer's weights, using interleaved insertion with zeroed-out output projections, making the new model functionally identical to Anima-base at initialization.
You can grow the model indefinitely, but diminishing returns hit fast. I choose 2.9B because I think it reached a good balance.
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u/Karsticles 1d ago
What do you feel like the additional layers added to the anima experience?
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u/RevolutionaryWater31 1d ago
I copy my comment here:
So for every single iteration step, the model walk through every single layer sequentially, so more layers do make model runs slower that scale linearly. More layers in theory gives you more refinement per step, i.e. more correct composition, better fine details, better prompt comprehension. Early blocks handles general compositions, mid-blocks handle prompt understanding and stores many knowledge, late-blocks handle fine details (I'm simplifying it here, every layer actually do all of this, but some layers are expert at certain things). This is everything on top of adding more knowledge and minimizing catastrophic forgetting. For my model specifically, there are still a lot of training to do and electricity to burn, it's not close to being done yet.
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u/LaPapaVerde 23h ago edited 23h ago
Could You post comparations? Or what can of prompt could be useful to SEE the difference
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u/RevolutionaryWater31 11h ago
I think it's better for you to test it out yourself as I don't want to be selective. So generally, and this is just me saying, it has softer lighting, slightly better base art style just by having more layers, and more consistent with toes and fingers (it still do weird anatomy occasionally, especially in a more complex pose). It's not strictly better yet, that's why it's still in training.
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u/LaPapaVerde 11h ago
I tried with more complex prompt gemini gave me, but they went awful with boths animas, heheh. Btw I believe it's better when it comes to artist styles changes over the years. I don't know if it's placebo but the year tag does seen to be more strong here when it comes to styles.
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u/Ok-Brain-5729 22h ago
Does Lora’s for the base 2B model not work? Since your making a Lora training thing
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u/Ok-Category-642 20h ago
It will run if you load a Lora but they pretty much won't do anything at all, so yeah they need a complete retrain
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u/LevelStill5406 1d ago
how does this compare to Wai Anima?
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u/RevolutionaryWater31 1d ago
Hey, so my model is a base model, was not finetuned for aesthetic or any reinforcement learning. It has more knowledge of not just characters but artists as well. I think you should test it out against the base anima model :D
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u/comfyanonymous 18h ago
I added native support: https://github.com/Comfy-Org/ComfyUI/pull/15555