ANIMA 1.0 (Anima Base Ultra) Text-to-Image Workflows

Anime/illustration text-to-image (ANIMA 1.0, ~2B Cosmos DiT).

How to install

How to install

  1. Setup differs for this server — follow the Installation part of the README below.
  2. Claude Code: claude mcp add <name> -- <command>.
  3. Claude Desktop / Cursor: add it under mcpServers in the MCP config file.
Claude Code — installs the whole folder, not just SKILL.md
npx degit artokun/comfyui-mcp/plugin/skills/anima-base#main ~/.claude/skills/anima-base

For one project only, change the path to .claude/skills/anima-base.

This one runs on your machine and can reach your files. Read the README below before you connect it.

Not working?
  • Check which app you pasted it into — the steps above name the right one.
  • Some skills need the paid tier of Claude or ChatGPT.
Step-by-step guide with screenshots · Ask in the forum

Paste into Claude, ChatGPT or Cursor.

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ANIMA 1.0 (Anima Base Ultra) Text-to-Image Workflows

Overview

Anima is a ~2B-parameter anime / illustration text-to-image base model from CircleStone Labs, made in collaboration with Comfy Org. It is not SDXL-lineage. The architecture is NVIDIA Cosmos-Predict2-2B-Text2Image (a DiT / flow model), trained on several million anime images plus ~800k non-anime artistic images. It suits anime, manga, and illustrated characters and styles, not realism.

Key traits:

  • Accepts Danbooru-style tags and/or natural language in the same prompt.
  • Very low VRAM. It generates and trains on <6GB VRAM and runs on any PC that can run SDXL/Illustrious.
  • License: CircleStone Labs Non-Commercial License, with NVIDIA Open Model License terms on the weights and derivatives. Generated images are usable commercially per the model card. Verify the current license text before relying on this.

ComfyUI loads it with standard split-file loaders, not a single checkpoint:

Component Node Model file Folder Notes
Diffusion model UNETLoader anima-base-v1.0.safetensors models/diffusion_models/ weight_dtype default; ~4GB fp
Text encoder CLIPLoader qwen_3_06b_base.safetensors models/text_encoders/ Qwen3-0.6B base; type": "stable_diffusion" in this pack
VAE VAELoader qwen_image_vae.safetensors models/vae/ Qwen-Image VAE (~254MB)

Verified from the pack's workflow JSON: CLIPLoader widget values are ["qwen_3_06b_base.safetensors", "stable_diffusion", "default"]. The HF model card describes standard loaders; the exact CLIP type string stable_diffusion is what the Aitrepreneur "Anima Base Ultra" workflow ships. Use it as-is.

Installation

The "Anima Base Ultra" pack (by Aitrepreneur) installs custom nodes and downloads all models. Models are mirrored on https://huggingface.co/Aitrepreneur/FLX/resolve/main; the official source is https://huggingface.co/circlestone-labs/Anima.

Custom nodes (git clone into ComfyUI/custom_nodes/)

Node pack Repo Used for
ComfyUI-Manager https://github.com/ltdrdata/ComfyUI-Manager.git management
ComfyUI-Impact-Pack https://github.com/ltdrdata/ComfyUI-Impact-Pack FaceDetailer / EditDetailerPipe
ComfyUI-Impact-Subpack https://github.com/ltdrdata/ComfyUI-Impact-Subpack UltralyticsDetectorProvider
rgthree-comfy https://github.com/rgthree/rgthree-comfy Power Lora Loader, Fast Groups, Any Switch
ComfyUI-KJNodes https://github.com/kijai/ComfyUI-KJNodes helpers
ComfyUI_UltimateSDUpscale https://github.com/ssitu/ComfyUI_UltimateSDUpscale tiled upscaling
ComfyUI_tinyterraNodes https://github.com/TinyTerra/ComfyUI_tinyterraNodes ttN seed
comfyui_controlnet_aux https://github.com/Fannovel16/comfyui_controlnet_aux DWPreprocessor, DepthAnythingV2
ComfyUI-Anima-LLLite https://github.com/kohya-ss/ComfyUI-Anima-LLLite AnimaLLLiteApply_sdscripts (ControlNet + inpainting)

Models (download URLs from the pack's .bat / .sh)

Base $HF = https://huggingface.co/Aitrepreneur/FLX/resolve/main, $YOLO11 = https://huggingface.co/Ultralytics/YOLO11/resolve/main. Append ?download=true.

Folder File Source
diffusion_models/ anima-base-v1.0.safetensors $HF
text_encoders/ qwen_3_06b_base.safetensors $HF
vae/ qwen_image_vae.safetensors $HF
controlnet/ anima-lllite-inpainting-v1.safetensors $HF
controlnet/ anima-lllite-depth-1.safetensors $HF
controlnet/ anima-lllite-lineart-1.safetensors $HF
controlnet/ anima-lllite-pose-1.safetensors $HF
controlnet/ anima-lllite-any-test-like-1-step2000.safetensors $HF
loras/ anima-turbo-lora-v0.1.safetensors $HF
loras/ anima-highres-aesthetic-boost.safetensors $HF
loras/ anima-preview-3-masterpieces-v5.safetensors $HF
loras/ anima_p3_rdbt_v0.29.b.122.safetensors $HF
upscale_models/ 4x_foolhardy_Remacri.pth, 4x-ClearRealityV1.pth $HF
ultralytics/bbox/ face_yolov9c.pt, hand_yolov9c.pt, Eyeful_v2-Paired.pt $HF
ultralytics/segm/ ntd11_anime_nsfw_segm_v5-variant1.pt $HF
ultralytics/segm/ yolo11m-seg.pt $YOLO11
sams/ sam_vit_b_01ec64.pth $HF

comfyui_controlnet_aux fetches the DWPreprocessor/DepthAnythingV2 aux models (dw-ll_ucoco_384_bs5.torchscript.pt, yolox_l.onnx, depth_anything_v2_vitl.pth) on first use.

Key Nodes

Loaders

{
  "1": { "class_type": "UNETLoader", "inputs": { "unet_name": "anima-base-v1.0.safetensors", "weight_dtype": "default" }},
  "2": { "class_type": "CLIPLoader", "inputs": { "clip_name": "qwen_3_06b_base.safetensors", "type": "stable_diffusion", "device": "default" }},
  "3": { "class_type": "VAELoader", "inputs": { "vae_name": "qwen_image_vae.safetensors" }}
}

Anima Turbo LoRA (the shipped default — 12-step fast mode)

The pack applies it with rgthree Power Lora Loader. The plain ComfyUI equivalent is LoraLoaderModelOnly:

{
  "class_type": "LoraLoaderModelOnly",
  "inputs": { "model": ["1", 0], "lora_name": "anima-turbo-lora-v0.1.safetensors", "strength_model": 1.0 }
}

The pack ships three other LoRAs you can toggle in Power Lora Loader: anima-highres-aesthetic-boost, anima-preview-3-masterpieces-v5, anima_p3_rdbt_v0.29.b.122. In the non-turbo groups these three are enabled and the turbo LoRA is off; in the turbo groups only the turbo LoRA is on.

AnimaLLLiteApply_sdscripts (ControlNet + inpainting — from ComfyUI-Anima-LLLite)

Patches the MODEL. Anima uses LLLite-style control, not standard ControlNetApply conditioning. Inputs: model, image, mask; widget order [lllite_name, strength, start_percent, end_percent, preserve_wrapper]; output: patched MODEL. ComfyUI core now owns the old ID AnimaLLLiteApply (different signature: a MODEL_PATCH from ModelPatchLoader, no mask), so this pack uses the kohya-ss node ID AnimaLLLiteApply_sdscripts.

{
  "class_type": "AnimaLLLiteApply_sdscripts",
  "inputs": {
    "model": ["<model>", 0],
    "image": ["<control_or_source_image>", 0],
    "mask": ["<mask>", 0],
    "lllite_name": "anima-lllite-pose-1.safetensors",
    "strength": 1.0, "start_percent": 0.0, "end_percent": 1.0,
    "preserve_wrapper": true
  }
}

Settings

The base model and the turbo-LoRA path want different settings:

Mode Steps CFG Sampler Scheduler Denoise Notes
Base (no turbo LoRA) 30–50 4–5 er_sde simple 1.0 Author-recommended for the base model
Turbo LoRA (shipped default) 12 1.0 er_sde simple 1.0 anima-turbo-lora-v0.1 enabled
Upscale pass (UltimateSDUpscale) 12 1.0 er_sde simple 0.28 4x_foolhardy_Remacri.pth, scale 2x

Sampler character, from the model card: er_sde gives a neutral style, flat colors, sharp lines; euler_ancestral gives softer, thinner lines; dpmpp_2m_sde_gpu is similar with more variety. The optional beta57 scheduler gives painterly looks.

Resolutions

The base model supports 512² to 1536². The pack recommends these to avoid distortion:

Aspect Resolution
1:1 1024x1024
3:4 896x1152
5:8 832x1216
9:16 768x1344
9:21 640x1536

Prompt Style

Anima accepts Danbooru tags and natural language together. The pack's recommended formula:

masterpiece, best quality, score_7, safe, highres, official art,
1girl, solo,
@artist name,
clean lineart, detailed eyes, soft shading,

A young anime woman with long silver hair and blue eyes stands in a rainy neon city at night.
She wears a black futuristic jacket with glowing blue details. Medium close-up, wet pavement
reflections, soft background blur, cinematic lighting.

The order is quality tags, then subject/count tags, then an optional @artist name, then anime style tags, then 2 to 4 natural-language sentences describing subject, outfit, pose, composition, background, lighting, and mood. Use lowercase tags with spaces (not underscores), except score tags like score_7. Artist tags use @artist name; browse names at the community Anima Style Explorer (https://thetacursed.github.io/Anima-Style-Explorer/).

Recommended negative prompt:

worst quality, low quality, score_1, score_2, score_3, artist name, bad anatomy, bad hands,
missing fingers, extra fingers, extra arms, extra legs, duplicate, twins, text, watermark,
signature, simple background

Unlike Flux/Qwen, Anima does use a real negative prompt via a second CLIPTextEncode (CFG > 1 in base mode).

Complete Workflow: Text-to-Image (Turbo, 12-step)

{
  "1": { "class_type": "UNETLoader", "inputs": { "unet_name": "anima-base-v1.0.safetensors", "weight_dtype": "default" }},
  "2": { "class_type": "CLIPLoader", "inputs": { "clip_name": "qwen_3_06b_base.safetensors", "type": "stable_diffusion", "device": "default" }},
  "3": { "class_type": "VAELoader", "inputs": { "vae_name": "qwen_image_vae.safetensors" }},
  "4": { "class_type": "LoraLoaderModelOnly", "inputs": { "model": ["1", 0], "lora_name": "anima-turbo-lora-v0.1.safetensors", "strength_model": 1.0 }},
  "5": { "class_type": "CLIPTextEncode", "inputs": { "clip": ["2", 0], "text": "masterpiece, best quality, score_7, safe, highres, official art, 1girl, solo, clean lineart, detailed eyes, soft shading,\n\nA young anime woman with long silver hair and blue eyes stands in a rainy neon city at night, cinematic lighting." }},
  "6": { "class_type": "CLIPTextEncode", "inputs": { "clip": ["2", 0], "text": "worst quality, low quality, score_1, score_2, score_3, bad anatomy, bad hands, extra fingers, text, watermark, signature, simple background" }},
  "7": { "class_type": "EmptyLatentImage", "inputs": { "width": 896, "height": 1152, "batch_size": 1 }},
  "8": { "class_type": "KSampler", "inputs": {
    "model": ["4", 0],
    "positive": ["5", 0],
    "negative": ["6", 0],
    "latent_image": ["7", 0],
    "seed": 42, "steps": 12, "cfg": 1, "sampler_name": "er_sde", "scheduler": "simple", "denoise": 1
  }},
  "9": { "class_type": "VAEDecode", "inputs": { "samples": ["8", 0], "vae": ["3", 0] }},
  "10": { "class_type": "SaveImage", "inputs": { "images": ["9", 0], "filename_prefix": "anima" }}
}

For the base-quality variant (no turbo), drop node 4 (feed ["1", 0] into KSampler), set steps: 30, cfg: 4.5. Optionally enable the three quality LoRAs (anima-highres-aesthetic-boost, anima-preview-3-masterpieces-v5, anima_p3_rdbt_v0.29.b.122) by chaining LoraLoaderModelOnly nodes.

Complete Workflow: Anime Inpainting (Anima-LLLite ControlNet)

The pack's "INPAINTING CONTROLNET" group loads an image with a painted mask, VAEEncodes it, applies SetLatentNoiseMask, patches the model with the inpainting LLLite (fed the same image and mask), then samples. The mask region is regenerated from the prompt and the rest is preserved.

{
  "1": { "class_type": "UNETLoader", "inputs": { "unet_name": "anima-base-v1.0.safetensors", "weight_dtype": "default" }},
  "2": { "class_type": "CLIPLoader", "inputs": { "clip_name": "qwen_3_06b_base.safetensors", "type": "stable_diffusion", "device": "default" }},
  "3": { "class_type": "VAELoader", "inputs": { "vae_name": "qwen_image_vae.safetensors" }},
  "4": { "class_type": "LoraLoaderModelOnly", "inputs": { "model": ["1", 0], "lora_name": "anima-turbo-lora-v0.1.safetensors", "strength_model": 1.0 }},
  "5": { "class_type": "LoadImage", "inputs": { "image": "<masked_image.png>" }},
  "6": { "class_type": "AnimaLLLiteApply_sdscripts", "inputs": {
    "model": ["4", 0], "image": ["5", 0], "mask": ["5", 1],
    "lllite_name": "anima-lllite-inpainting-v1.safetensors",
    "strength": 1.0, "start_percent": 0.0, "end_percent": 1.0,
    "preserve_wrapper": true
  }},
  "7": { "class_type": "CLIPTextEncode", "inputs": { "clip": ["2", 0], "text": "<what to paint into the masked area>" }},
  "8": { "class_type": "CLIPTextEncode", "inputs": { "clip": ["2", 0], "text": "worst quality, low quality, bad anatomy, text, watermark" }},
  "9": { "class_type": "VAEEncode", "inputs": { "pixels": ["5", 0], "vae": ["3", 0] }},
  "10": { "class_type": "SetLatentNoiseMask", "inputs": { "samples": ["9", 0], "mask": ["5", 1] }},
  "11": { "class_type": "KSampler", "inputs": {
    "model": ["6", 0],
    "positive": ["7", 0],
    "negative": ["8", 0],
    "latent_image": ["10", 0],
    "seed": 42, "steps": 12, "cfg": 1, "sampler_name": "er_sde", "scheduler": "simple", "denoise": 1
  }},
  "12": { "class_type": "VAEDecode", "inputs": { "samples": ["11", 0], "vae": ["3", 0] }},
  "13": { "class_type": "SaveImage", "inputs": { "images": ["12", 0], "filename_prefix": "anima_inpaint" }}
}

The other LLLite ControlNets use the same AnimaLLLiteApply_sdscripts node. Swap lllite_name and feed a preprocessed control image; the mask can be a full-white/blank mask when not inpainting:

  • anima-lllite-pose-1.safetensorsDWPreprocessor (OpenPose)
  • anima-lllite-depth-1.safetensorsDepthAnythingV2Preprocessor
  • anima-lllite-lineart-1.safetensors / anima-lllite-any-test-like-1-step2000.safetensors ← lineart / generic control

Upscaling (optional)

The pack upscales with UltimateSDUpscale (4x_foolhardy_Remacri.pth, 2x, denoise 0.28, 12 steps, er_sde/simple) and refines faces, hands, and eyes with Impact-Pack FaceDetailer driven by UltralyticsDetectorProvider (face_yolov9c.pt, hand_yolov9c.pt, Eyeful_v2-Paired.pt) + SAM (sam_vit_b_01ec64.pth).

VRAM

  • Anima is ~2B params, so it generates in <6GB VRAM and runs anywhere SDXL/Illustrious runs.
  • The text encoder (Qwen3-0.6B) and VAE are both small.
  • A GGUF quantized build exists for even lower memory (Abiray/Anima-base-v1.0-GGUF). It needs a GGUF loader node (e.g. ComfyUI-GGUF), which this pack does not include. Unverified against this workflow.

Troubleshooting

  1. Weird/distorted images. Use a recommended resolution (1024x1024, 896x1152, 832x1216, 768x1344, 640x1536).
  2. Turbo result looks washed/flat. That's turbo at CFG 1. For max quality switch to base mode (drop turbo LoRA, 30 to 50 steps, CFG 4 to 5).
  3. AnimaLLLiteApply_sdscripts missing. Install ComfyUI-Anima-LLLite; it is not a standard ControlNet node. Do not add core AnimaLLLiteApply — that ID now belongs to ComfyUI and has a different input signature.
  4. CLIP loads but output is garbage. Confirm CLIPLoader type is stable_diffusion and the file is qwen_3_06b_base.safetensors (the Qwen3-0.6B base, not the chat/edit Qwen models).
  5. Inpainting ignores the mask. Ensure both SetLatentNoiseMask and the inpainting AnimaLLLiteApply_sdscripts receive the painted mask, and encode the source image with VAEEncode. Denoise 1.0 is fine because the noise mask preserves unmasked pixels.

Training custom LoRAs

To train your own Anima LoRA (character/style) on <6GB VRAM, use the Citron Anima LoRA Trainer; see the anima-lora-trainer skill. Trained .safetensors LoRAs drop into models/loras/ and load via Power Lora Loader / LoraLoaderModelOnly exactly like the bundled LoRAs above.

Sources

  • Official: model weights at https://huggingface.co/circlestone-labs/Anima; ComfyUI-Anima-LLLite README documents the node ID AnimaLLLiteApply_sdscripts after the core AnimaLLLiteApply collision. No vendor prompting guide cited.
  • Empirical: tag-order / @artist prompting and sampler wiring from working graphs; Anima Style Explorer is community, not vendor docs.
1---
2name: anima-base
3description: Anime/illustration text-to-image (ANIMA 1.0, ~2B Cosmos DiT). Use for anime, manga, illustrated characters; accepts Danbooru tags + natural language; runs/trains on <6GB VRAM; includes anime inpainting via Anima-LLLite ControlNet
4globs:
5 - "**/*.json"
6---
7 
8# ANIMA 1.0 (Anima Base Ultra) Text-to-Image Workflows
9 
10## Overview
11 
12Anima is a ~2B-parameter anime / illustration text-to-image base model from CircleStone Labs, made in collaboration with Comfy Org. It is not SDXL-lineage. The architecture is NVIDIA Cosmos-Predict2-2B-Text2Image (a DiT / flow model), trained on several million anime images plus ~800k non-anime artistic images. It suits anime, manga, and illustrated characters and styles, not realism.
13 
14Key traits:
15- Accepts Danbooru-style tags and/or natural language in the same prompt.
16- Very low VRAM. It generates and trains on <6GB VRAM and runs on any PC that can run SDXL/Illustrious.
17- License: CircleStone Labs Non-Commercial License, with NVIDIA Open Model License terms on the weights and derivatives. Generated images are usable commercially per the model card. Verify the current license text before relying on this.
18 
19ComfyUI loads it with standard split-file loaders, not a single checkpoint:
20 
21| Component | Node | Model file | Folder | Notes |
22|-----------|------|-----------|--------|-------|
23| **Diffusion model** | `UNETLoader` | `anima-base-v1.0.safetensors` | `models/diffusion_models/` | weight_dtype `default`; ~4GB fp |
24| **Text encoder** | `CLIPLoader` | `qwen_3_06b_base.safetensors` | `models/text_encoders/` | Qwen3-0.6B base; **`type": "stable_diffusion"`** in this pack |
25| **VAE** | `VAELoader` | `qwen_image_vae.safetensors` | `models/vae/` | Qwen-Image VAE (~254MB) |
26 
27> Verified from the pack's workflow JSON: `CLIPLoader` widget values are `["qwen_3_06b_base.safetensors", "stable_diffusion", "default"]`. The HF model card describes standard loaders; the exact CLIP `type` string `stable_diffusion` is what the Aitrepreneur "Anima Base Ultra" workflow ships. Use it as-is.
28 
29## Installation
30 
31The "Anima Base Ultra" pack (by Aitrepreneur) installs custom nodes and downloads all models. Models are mirrored on `https://huggingface.co/Aitrepreneur/FLX/resolve/main`; the official source is `https://huggingface.co/circlestone-labs/Anima`.
32 
33### Custom nodes (git clone into `ComfyUI/custom_nodes/`)
34 
35| Node pack | Repo | Used for |
36|-----------|------|----------|
37| ComfyUI-Manager | `https://github.com/ltdrdata/ComfyUI-Manager.git` | management |
38| ComfyUI-Impact-Pack | `https://github.com/ltdrdata/ComfyUI-Impact-Pack` | FaceDetailer / EditDetailerPipe |
39| ComfyUI-Impact-Subpack | `https://github.com/ltdrdata/ComfyUI-Impact-Subpack` | UltralyticsDetectorProvider |
40| rgthree-comfy | `https://github.com/rgthree/rgthree-comfy` | Power Lora Loader, Fast Groups, Any Switch |
41| ComfyUI-KJNodes | `https://github.com/kijai/ComfyUI-KJNodes` | helpers |
42| ComfyUI_UltimateSDUpscale | `https://github.com/ssitu/ComfyUI_UltimateSDUpscale` | tiled upscaling |
43| ComfyUI_tinyterraNodes | `https://github.com/TinyTerra/ComfyUI_tinyterraNodes` | ttN seed |
44| comfyui_controlnet_aux | `https://github.com/Fannovel16/comfyui_controlnet_aux` | DWPreprocessor, DepthAnythingV2 |
45| **ComfyUI-Anima-LLLite** | `https://github.com/kohya-ss/ComfyUI-Anima-LLLite` | **`AnimaLLLiteApply_sdscripts`** (ControlNet + inpainting) |
46 
47### Models (download URLs from the pack's .bat / .sh)
48 
49Base `$HF = https://huggingface.co/Aitrepreneur/FLX/resolve/main`, `$YOLO11 = https://huggingface.co/Ultralytics/YOLO11/resolve/main`. Append `?download=true`.
50 
51| Folder | File | Source |
52|--------|------|--------|
53| `diffusion_models/` | `anima-base-v1.0.safetensors` | `$HF` |
54| `text_encoders/` | `qwen_3_06b_base.safetensors` | `$HF` |
55| `vae/` | `qwen_image_vae.safetensors` | `$HF` |
56| `controlnet/` | `anima-lllite-inpainting-v1.safetensors` | `$HF` |
57| `controlnet/` | `anima-lllite-depth-1.safetensors` | `$HF` |
58| `controlnet/` | `anima-lllite-lineart-1.safetensors` | `$HF` |
59| `controlnet/` | `anima-lllite-pose-1.safetensors` | `$HF` |
60| `controlnet/` | `anima-lllite-any-test-like-1-step2000.safetensors` | `$HF` |
61| `loras/` | `anima-turbo-lora-v0.1.safetensors` | `$HF` |
62| `loras/` | `anima-highres-aesthetic-boost.safetensors` | `$HF` |
63| `loras/` | `anima-preview-3-masterpieces-v5.safetensors` | `$HF` |
64| `loras/` | `anima_p3_rdbt_v0.29.b.122.safetensors` | `$HF` |
65| `upscale_models/` | `4x_foolhardy_Remacri.pth`, `4x-ClearRealityV1.pth` | `$HF` |
66| `ultralytics/bbox/` | `face_yolov9c.pt`, `hand_yolov9c.pt`, `Eyeful_v2-Paired.pt` | `$HF` |
67| `ultralytics/segm/` | `ntd11_anime_nsfw_segm_v5-variant1.pt` | `$HF` |
68| `ultralytics/segm/` | `yolo11m-seg.pt` | `$YOLO11` |
69| `sams/` | `sam_vit_b_01ec64.pth` | `$HF` |
70 
71`comfyui_controlnet_aux` fetches the DWPreprocessor/DepthAnythingV2 aux models (`dw-ll_ucoco_384_bs5.torchscript.pt`, `yolox_l.onnx`, `depth_anything_v2_vitl.pth`) on first use.
72 
73## Key Nodes
74 
75### Loaders
76```json
77{
78 "1": { "class_type": "UNETLoader", "inputs": { "unet_name": "anima-base-v1.0.safetensors", "weight_dtype": "default" }},
79 "2": { "class_type": "CLIPLoader", "inputs": { "clip_name": "qwen_3_06b_base.safetensors", "type": "stable_diffusion", "device": "default" }},
80 "3": { "class_type": "VAELoader", "inputs": { "vae_name": "qwen_image_vae.safetensors" }}
81}
82```
83 
84### Anima Turbo LoRA (the shipped default — 12-step fast mode)
85The pack applies it with rgthree `Power Lora Loader`. The plain ComfyUI equivalent is `LoraLoaderModelOnly`:
86```json
87{
88 "class_type": "LoraLoaderModelOnly",
89 "inputs": { "model": ["1", 0], "lora_name": "anima-turbo-lora-v0.1.safetensors", "strength_model": 1.0 }
90}
91```
92The pack ships three other LoRAs you can toggle in Power Lora Loader: `anima-highres-aesthetic-boost`, `anima-preview-3-masterpieces-v5`, `anima_p3_rdbt_v0.29.b.122`. In the non-turbo groups these three are enabled and the turbo LoRA is off; in the turbo groups only the turbo LoRA is on.
93 
94### AnimaLLLiteApply_sdscripts (ControlNet + inpainting — from ComfyUI-Anima-LLLite)
95Patches the MODEL. Anima uses LLLite-style control, not standard `ControlNetApply` conditioning. Inputs: `model`, `image`, `mask`; widget order `[lllite_name, strength, start_percent, end_percent, preserve_wrapper]`; output: patched `MODEL`. ComfyUI core now owns the old ID `AnimaLLLiteApply` (different signature: a `MODEL_PATCH` from `ModelPatchLoader`, no mask), so this pack uses the kohya-ss node ID `AnimaLLLiteApply_sdscripts`.
96```json
97{
98 "class_type": "AnimaLLLiteApply_sdscripts",
99 "inputs": {
100 "model": ["<model>", 0],
101 "image": ["<control_or_source_image>", 0],
102 "mask": ["<mask>", 0],
103 "lllite_name": "anima-lllite-pose-1.safetensors",
104 "strength": 1.0, "start_percent": 0.0, "end_percent": 1.0,
105 "preserve_wrapper": true
106 }
107}
108```
109 
110## Settings
111 
112The base model and the turbo-LoRA path want different settings:
113 
114| Mode | Steps | CFG | Sampler | Scheduler | Denoise | Notes |
115|------|-------|-----|---------|-----------|---------|-------|
116| **Base (no turbo LoRA)** | 30–50 | 4–5 | `er_sde` | `simple` | 1.0 | Author-recommended for the base model |
117| **Turbo LoRA (shipped default)** | 12 | 1.0 | `er_sde` | `simple` | 1.0 | `anima-turbo-lora-v0.1` enabled |
118| Upscale pass (UltimateSDUpscale) | 12 | 1.0 | `er_sde` | `simple` | 0.28 | `4x_foolhardy_Remacri.pth`, scale 2x |
119 
120Sampler character, from the model card: `er_sde` gives a neutral style, flat colors, sharp lines; `euler_ancestral` gives softer, thinner lines; `dpmpp_2m_sde_gpu` is similar with more variety. The optional `beta57` scheduler gives painterly looks.
121 
122## Resolutions
123 
124The base model supports 512² to 1536². The pack recommends these to avoid distortion:
125 
126| Aspect | Resolution |
127|--------|-----------|
128| 1:1 | 1024x1024 |
129| 3:4 | 896x1152 |
130| 5:8 | 832x1216 |
131| 9:16 | 768x1344 |
132| 9:21 | 640x1536 |
133 
134## Prompt Style
135 
136Anima accepts Danbooru tags and natural language together. The pack's recommended formula:
137 
138```
139masterpiece, best quality, score_7, safe, highres, official art,
1401girl, solo,
141@artist name,
142clean lineart, detailed eyes, soft shading,
143 
144A young anime woman with long silver hair and blue eyes stands in a rainy neon city at night.
145She wears a black futuristic jacket with glowing blue details. Medium close-up, wet pavement
146reflections, soft background blur, cinematic lighting.
147```
148 
149The order is quality tags, then subject/count tags, then an optional `@artist name`, then anime style tags, then 2 to 4 natural-language sentences describing subject, outfit, pose, composition, background, lighting, and mood. Use lowercase tags with spaces (not underscores), except score tags like `score_7`. Artist tags use `@artist name`; browse names at the community Anima Style Explorer (`https://thetacursed.github.io/Anima-Style-Explorer/`).
150 
151Recommended negative prompt:
152```
153worst quality, low quality, score_1, score_2, score_3, artist name, bad anatomy, bad hands,
154missing fingers, extra fingers, extra arms, extra legs, duplicate, twins, text, watermark,
155signature, simple background
156```
157Unlike Flux/Qwen, Anima does use a real negative prompt via a second `CLIPTextEncode` (CFG > 1 in base mode).
158 
159## Complete Workflow: Text-to-Image (Turbo, 12-step)
160 
161```json
162{
163 "1": { "class_type": "UNETLoader", "inputs": { "unet_name": "anima-base-v1.0.safetensors", "weight_dtype": "default" }},
164 "2": { "class_type": "CLIPLoader", "inputs": { "clip_name": "qwen_3_06b_base.safetensors", "type": "stable_diffusion", "device": "default" }},
165 "3": { "class_type": "VAELoader", "inputs": { "vae_name": "qwen_image_vae.safetensors" }},
166 "4": { "class_type": "LoraLoaderModelOnly", "inputs": { "model": ["1", 0], "lora_name": "anima-turbo-lora-v0.1.safetensors", "strength_model": 1.0 }},
167 "5": { "class_type": "CLIPTextEncode", "inputs": { "clip": ["2", 0], "text": "masterpiece, best quality, score_7, safe, highres, official art, 1girl, solo, clean lineart, detailed eyes, soft shading,\n\nA young anime woman with long silver hair and blue eyes stands in a rainy neon city at night, cinematic lighting." }},
168 "6": { "class_type": "CLIPTextEncode", "inputs": { "clip": ["2", 0], "text": "worst quality, low quality, score_1, score_2, score_3, bad anatomy, bad hands, extra fingers, text, watermark, signature, simple background" }},
169 "7": { "class_type": "EmptyLatentImage", "inputs": { "width": 896, "height": 1152, "batch_size": 1 }},
170 "8": { "class_type": "KSampler", "inputs": {
171 "model": ["4", 0],
172 "positive": ["5", 0],
173 "negative": ["6", 0],
174 "latent_image": ["7", 0],
175 "seed": 42, "steps": 12, "cfg": 1, "sampler_name": "er_sde", "scheduler": "simple", "denoise": 1
176 }},
177 "9": { "class_type": "VAEDecode", "inputs": { "samples": ["8", 0], "vae": ["3", 0] }},
178 "10": { "class_type": "SaveImage", "inputs": { "images": ["9", 0], "filename_prefix": "anima" }}
179}
180```
181 
182For the base-quality variant (no turbo), drop node 4 (feed `["1", 0]` into KSampler), set `steps: 30`, `cfg: 4.5`. Optionally enable the three quality LoRAs (`anima-highres-aesthetic-boost`, `anima-preview-3-masterpieces-v5`, `anima_p3_rdbt_v0.29.b.122`) by chaining `LoraLoaderModelOnly` nodes.
183 
184## Complete Workflow: Anime Inpainting (Anima-LLLite ControlNet)
185 
186The pack's "INPAINTING CONTROLNET" group loads an image with a painted mask, `VAEEncode`s it, applies `SetLatentNoiseMask`, patches the model with the inpainting LLLite (fed the same image and mask), then samples. The mask region is regenerated from the prompt and the rest is preserved.
187 
188```json
189{
190 "1": { "class_type": "UNETLoader", "inputs": { "unet_name": "anima-base-v1.0.safetensors", "weight_dtype": "default" }},
191 "2": { "class_type": "CLIPLoader", "inputs": { "clip_name": "qwen_3_06b_base.safetensors", "type": "stable_diffusion", "device": "default" }},
192 "3": { "class_type": "VAELoader", "inputs": { "vae_name": "qwen_image_vae.safetensors" }},
193 "4": { "class_type": "LoraLoaderModelOnly", "inputs": { "model": ["1", 0], "lora_name": "anima-turbo-lora-v0.1.safetensors", "strength_model": 1.0 }},
194 "5": { "class_type": "LoadImage", "inputs": { "image": "<masked_image.png>" }},
195 "6": { "class_type": "AnimaLLLiteApply_sdscripts", "inputs": {
196 "model": ["4", 0], "image": ["5", 0], "mask": ["5", 1],
197 "lllite_name": "anima-lllite-inpainting-v1.safetensors",
198 "strength": 1.0, "start_percent": 0.0, "end_percent": 1.0,
199 "preserve_wrapper": true
200 }},
201 "7": { "class_type": "CLIPTextEncode", "inputs": { "clip": ["2", 0], "text": "<what to paint into the masked area>" }},
202 "8": { "class_type": "CLIPTextEncode", "inputs": { "clip": ["2", 0], "text": "worst quality, low quality, bad anatomy, text, watermark" }},
203 "9": { "class_type": "VAEEncode", "inputs": { "pixels": ["5", 0], "vae": ["3", 0] }},
204 "10": { "class_type": "SetLatentNoiseMask", "inputs": { "samples": ["9", 0], "mask": ["5", 1] }},
205 "11": { "class_type": "KSampler", "inputs": {
206 "model": ["6", 0],
207 "positive": ["7", 0],
208 "negative": ["8", 0],
209 "latent_image": ["10", 0],
210 "seed": 42, "steps": 12, "cfg": 1, "sampler_name": "er_sde", "scheduler": "simple", "denoise": 1
211 }},
212 "12": { "class_type": "VAEDecode", "inputs": { "samples": ["11", 0], "vae": ["3", 0] }},
213 "13": { "class_type": "SaveImage", "inputs": { "images": ["12", 0], "filename_prefix": "anima_inpaint" }}
214}
215```
216 
217The other LLLite ControlNets use the same `AnimaLLLiteApply_sdscripts` node. Swap `lllite_name` and feed a preprocessed control image; the mask can be a full-white/blank mask when not inpainting:
218- `anima-lllite-pose-1.safetensors``DWPreprocessor` (OpenPose)
219- `anima-lllite-depth-1.safetensors``DepthAnythingV2Preprocessor`
220- `anima-lllite-lineart-1.safetensors` / `anima-lllite-any-test-like-1-step2000.safetensors` ← lineart / generic control
221 
222## Upscaling (optional)
223 
224The pack upscales with `UltimateSDUpscale` (`4x_foolhardy_Remacri.pth`, 2x, denoise 0.28, 12 steps, er_sde/simple) and refines faces, hands, and eyes with Impact-Pack `FaceDetailer` driven by `UltralyticsDetectorProvider` (`face_yolov9c.pt`, `hand_yolov9c.pt`, `Eyeful_v2-Paired.pt`) + SAM (`sam_vit_b_01ec64.pth`).
225 
226## VRAM
227 
228- Anima is ~2B params, so it generates in <6GB VRAM and runs anywhere SDXL/Illustrious runs.
229- The text encoder (Qwen3-0.6B) and VAE are both small.
230- A GGUF quantized build exists for even lower memory (`Abiray/Anima-base-v1.0-GGUF`). It needs a GGUF loader node (e.g. ComfyUI-GGUF), which this pack does not include. *Unverified against this workflow.*
231 
232## Troubleshooting
233 
2341. **Weird/distorted images.** Use a recommended resolution (1024x1024, 896x1152, 832x1216, 768x1344, 640x1536).
2352. **Turbo result looks washed/flat.** That's turbo at CFG 1. For max quality switch to base mode (drop turbo LoRA, 30 to 50 steps, CFG 4 to 5).
2363. **`AnimaLLLiteApply_sdscripts` missing.** Install `ComfyUI-Anima-LLLite`; it is not a standard ControlNet node. Do not add core `AnimaLLLiteApply` — that ID now belongs to ComfyUI and has a different input signature.
2374. **CLIP loads but output is garbage.** Confirm `CLIPLoader` `type` is `stable_diffusion` and the file is `qwen_3_06b_base.safetensors` (the Qwen3-0.6B *base*, not the chat/edit Qwen models).
2385. **Inpainting ignores the mask.** Ensure both `SetLatentNoiseMask` and the inpainting `AnimaLLLiteApply_sdscripts` receive the painted mask, and encode the *source* image with `VAEEncode`. Denoise 1.0 is fine because the noise mask preserves unmasked pixels.
239 
240## Training custom LoRAs
241 
242To train your own Anima LoRA (character/style) on <6GB VRAM, use the Citron Anima LoRA Trainer; see the `anima-lora-trainer` skill. Trained `.safetensors` LoRAs drop into `models/loras/` and load via `Power Lora Loader` / `LoraLoaderModelOnly` exactly like the bundled LoRAs above.
243 
244## Sources
245 
246- **Official:** model weights at https://huggingface.co/circlestone-labs/Anima; ComfyUI-Anima-LLLite README documents the node ID `AnimaLLLiteApply_sdscripts` after the core `AnimaLLLiteApply` collision. No vendor prompting guide cited.
247- **Empirical:** tag-order / @artist prompting and sampler wiring from working graphs; Anima Style Explorer is community, not vendor docs.
248 

Discussion

From GitHub

1 comment on 1 thread

Claimed 2026-09-02T20:05Z — dispatched to a fix agent (claude autopilot, pid 24308). Taking the converter fix: `isWidgetInput()`/`isPositionalWidgetSpec()` in `src/services/workflow-converter.ts` classify a `["STRING", {forceInput: true}]` spec as a positional widget, so the UI→API mapper consumes a `widgets_values` slot for an input the frontend never rendered a widget for — shifting every later widget by one. Will pin it with a test that fails when the guard is removed, in both conversion directions.

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