Anima-turbo-v1.0-GGUF
This is a quantized GGUF repository for the Anima-Turbo-v1.0 model originally created by CircleStone Labs. The model weights have been converted into F32 and subsequently quantized into multiple GGUF formats using a patched version of llama.cpp to enable efficient CPU and GPU-offloaded image generation in ComfyUI.
🌟 Model Overview
- Original Model: circlestone-labs/Anima
- Architecture: 2 Billion parameter text-to-image model. It is built on the
nvidia/Cosmos-Predict2-2B-Text2Imagebase. - Variant: Turbo v1.0 (A distilled version optimized for fast, low-step generation).
- Focus: It is focused mainly on anime concepts, characters, and styles. The model is designed for making illustrations and artistic images, and will not work well at realism.
💻 Hardware Compatibility & File Sizes
Select the quantization that best matches your system's RAM/VRAM constraints. Q4_K_M or Q5_K_M are generally recommended as the best balance of speed and visual fidelity.
| Bit Depth | Quantization Type | File Size |
|---|---|---|
| 3-bit | Q3_K_M | 1.02 GB |
| 4-bit | Q4_K_S | 1.27 GB |
| 4-bit | Q4_K_M | 1.38 GB |
| 5-bit | Q5_K_M | 1.56 GB |
| 6-bit | Q6_K | 1.74 GB |
| 8-bit | Q8_0 | 2.24 GB |
⚙️ How to Use in ComfyUI
1. Requirements
- Update ComfyUI to
v0.14.1or higher. - Install the
ComfyUI-GGUFcustom node to enable theUnetLoaderGGUFnode.
2. File Placement
Ensure you download the supplementary files located in this repository's split_files directories and place them into your local ComfyUI folders:
- Diffusion Model (GGUF): Place your chosen
anima-turbo-v1.0-[Quant].gguffile intoComfyUI/models/diffusion_models(or theunetfolder). - Text Encoder: Place
qwen_3_06b_base.safetensorsintoComfyUI/models/text_encoders. - VAE: Place
qwen_image_vae.safetensorsintoComfyUI/models/vae.
3. Turbo Generation Settings
Because this is the distilled Turbo version of Anima, it relies on specific, highly restricted parameters to function correctly:
- Steps:
8 to 12 - CFG Scale:
1.0(Do not use high CFG with the Turbo variant). - Sampler: The
eulersampler is highly recommended with the Turbo version, as it is naturally more stable. - Resolution: Works at resolutions between 512x512 and 1536x1536 pixels.
4. Prompting Guide
The model is trained on Danbooru-style tags, natural language captions, and combinations of tags and captions.
Syntax & Formatting:
- Use lowercase for tags, and spaces instead of underscores.
- Score tags are the only tags that use underscores.
Prefixes:
- Recommended Positive Prefix:
masterpiece, best quality, score_7, safe, - Recommended Negative Prompt:
worst quality, low quality, score_1, score_2, score_3, artist name, blurry, jpeg artifacts, chromatic aberration
Natural Language Tips:
- If using pure natural language, more descriptive is better.
- Aim for at least 2 sentences.
- Extremely short prompts can give unexpected results.
🌳 Model Tree & Lineage
- Base Architecture:
nvidia/Cosmos-Predict2-2B-Text2Image - Fine-tuned / Distilled Version:
circlestone-labs/Anima(Turbo v1.0 variant) - Quantized Version:
Abiray/Anima-turbo-v1.0-GGUF(This repository)