Sign In

16-step Acc LoRA | Anima

38

Updated: Oct 12, 2026

base model

Not recently loaded

Download

1 variant available

fp16 SafeTensor

anima_base_v1_acc_lora_by_reakaakasky_v2.4.safetensors

Half precision, best balance • 46.11 MB

Verified:

Type
LoRA
Stats

479

38

17

Reviews
Published

Sep 27, 2026

Base Model
Hash
AutoV20AFA842BBE

The Anima Model is licensed by CircleStone Labs LLC. Copyright CircleStone Labs LLC. IN NO EVENT SHALL CIRCLESTONE LABS LLC BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH USE OF THIS MODEL.

Built on NVIDIA Cosmos

out-_16856_.webp

Anima acc lora

A 16-step distillation LoRA.

Settings: CFG 1, 16 steps.

Works on any base ckpt.

It's not a better "turbo" LoRA, it's just another one, with different approach.


EDIT: About cover images:

Cover images are from my RDBT model (private version), highly stylized drawing, to demonstrate how distillation affects styles and details (losing details, there is no free lunch. And yes, I deliberately demonstrate how bad distillation could be)

When is distilled model recommended:

  • If you are looking for production level drawing and textures, or have a beefy GPU. Don't use distilled model.

  • If you are here for general anime styles, then this 16-step acc LoRA is OK. Most of the time you can get identical output, but 4x faster.

Difference between official turbo model:

  • More entropy. More details. More natural.

  • No detail/quality amplifier. Doesn't overwrite styles with a unified AI slop style. (TBH, I think this might be a bug in the official turbo. It adds artifacts and patterns. Overcooked probably.)


For users from my RBDT model:

I will stop releasing distilled RDBT ckpt from now on. I previously thought that if I distilled directly onto the fine-tuned ckpt, I could retain more detail. In reality, the difference is minimal to none. Therefore, I'm not wasting computational resources on each version.

v2.4 is trained/distilled with more compute and a much larger dataset. It has much better details than previous v2.3 distilled ckpt.