Anima Preview 2
UpdateMar 18, 2026 08:07PublishedMar 18, 2026 08:07
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Gugugaga
Type
UNet
Basic Model
Anima
Published time
Mar 18, 2026 08:07
File Signature
048d5cfb99f18d6be373247b83e227a0d6f2561656c706ce96ea5f1b51129a04
anima-preview2.safetensors
3.89 GB

Anima is a 2 billion parameter text-to-image model created via a collaboration between CircleStone Labs and Comfy Org. It is focused mainly on anime concepts, characters, and styles, but is also capable of generating a wide variety of other non-photorealistic content. The model is designed for making illustrations and artistic images, and will not work well at realism.

It is trained on several million anime images and about 800k non-anime artistic images. No synthetic data was used for training. The knowledge cut-off date for the anime training data is September 2025.

This preview version is an intermediate model checkpoint. The model is still training and the final version will improve, especially for fine details and overall aesthetics.

Installing and running

Get the text encoder and VAE from the HuggingFage page.

The model is natively supported in ComfyUI. The model files go in their respective folders inside your model directory:

anima-preview2.safetensors goes in ComfyUI/models/diffusion_models

qwen_3_06b_base.safetensors goes in ComfyUI/models/text_encoders

qwen_image_vae.safetensors goes in ComfyUI/models/vae (this is the Qwen-Image VAE, you might already have it)

Generation settings

The preview version should be used at about 1MP resolution. E.g. 1024x1024, 896x1152, 1152x896, etc.

30-50 steps, CFG 4-5.

A variety of samplers work. Some of my favorites:

er_sde: neutral style, flat colors, sharp lines. I use this as a reasonable default.

euler_a: Softer, thinner lines. Can sometimes tend towards a 2.5D look. CFG can be pushed a bit higher than other samplers without burning the image.

dpmpp_2m_sde_gpu: similar in style to er_sde but can produce more variety and be more "creative". Depending on the prompt it can get too wild sometimes.

Prompting

The model is trained on Danbooru-style tags, natural language captions, and combinations of tags and captions.

Tag order

[quality/meta/year/safety tags] [1girl/1boy/1other etc] [character] [series] [artist] [general tags]

Within each tag section, the tags can be in arbitrary order.

Quality tags

Human score based: masterpiece, best quality, good quality, normal quality, low quality, worst quality

PonyV7 aesthetic model based: score_9, score_8, ..., score_1

You can use either the human score quality tags, the aesthetic model tags, both together, or neither. All combinations work.

Time period tags

Specific year: year 2025, year 2024, ...

Period: newest, recent, mid, early, old

Meta tags

highres, absurdres, anime screenshot, jpeg artifacts, official art, etc

Safety tags

safe, sensitive, nsfw, explicit

Artist tags

Prefix artist with @. E.g. "@big chungus". You must put @ in front of the artist. The effect will be very weak if you don't.

Full tag example

year 2025, newest, normal quality, score_5, highres, safe, 1girl, oomuro sakurako, yuru yuri, @nnn yryr, smile, brown hair, hat, solo, fur-trimmed gloves, open mouth, long hair, gift box, fang, skirt, red gloves, blunt bangs, gloves, one eye closed, shirt, brown eyes, santa costume, red hat, skin fang, twitter username, white background, holding bag, fur trim, simple background, brown skirt, bag, gift bag, looking at viewer, santa hat, ;d, red shirt, box, gift, fur-trimmed headwear, holding, red capelet, holding box, capelet

Tag dropout

The model was trained with random tag dropout. You don't need to include every single relevant tag for the image.

Reposted from Huggingface

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