Anima Base

---
name: anima-base
description: 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
globs:
  - "**/*.json"
---

# 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
```json
{
  "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`:
```json
{
  "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`.
```json
{
  "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)

```json
{
  "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, `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.

```json
{
  "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.safetensors` ← `DWPreprocessor` (OpenPose)
- `anima-lllite-depth-1.safetensors` ← `DepthAnythingV2Preprocessor`
- `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.