ANIMA_BOOSTER for ComfyUI ⚡
The ultimate high-performance optimization suite designed to maximize inference speed and optimize the performance of the Anima DiT 2B model.
Delivers a massive 3.5× to 5.0× speedup with virtually no loss in visual quality!
> 💡 Ultimate Quality & Speed Combo:
> We highly recommend pairing this optimization suite with our companion node FLSampler (BSS) to perfectly restore any lost micro-details at lightning-fast speeds!
🔗 GitHub Repository (Full Guide & Docs): https://github.com/BlackSnowSkill/ANIMA_BOOSTER
🌟 Key Features (v1.3.0)
📥 Anima Checkpoint & UNET Loaders: Tailored loaders supporting standalone UNETs and full Checkpoints with built-in bfloat16 auto-detection.
⚡ Safe One-Click torch.compile: Stable JIT compilation toggle boosting speed by 20% to 40%.
🚀 SageAttention: Integrated accelerated 8-bit attention tailored for DiT.
🧠 Adaptive TeaCache: Timestep-aware latent caching that skips redundant calculations, protecting early structural steps.
🎨 BSS Premium UI: Elegant, high-contrast dark-matte interface with clean controls and zero intrusive tooltips.
📂 Quick Installation
1. Open ComfyUI Manager -> Install via Git URL.
2. Paste this URL: https://github.com/BlackSnowSkill/ANIMA_BOOSTER
3. Click Install and restart ComfyUI.
For detailed parameters, portable environment wheels, and manual installation, please refer to the GitHub README
☕ Support & License
Support Development: Support me and get exclusive models on Boosty!
License & Usage: © 2026 blacksnowskill (BSS). All rights reserved. This project is protected by copyright. Copying, distribution, merging, or use on other websites/repositories without explicit written permission is strictly prohibited.
Description
v1.2.0 - Stability & Performance Update.
This major update focuses on robust stability, codebase refactoring, and fixing scaling bugs for stochastic/SDE samplers. We have eliminated unstable components and made the suite bulletproof for everyday generation.
🆕 What's New in v1.2.0:
1. 🐛 TeaCache Fixed for SDE/Stochastic Samplers (e.g., er_sde, sde gpu)
The Issue: Stochastic samplers working on a sigma scale (like [14.6 .. 0.0]) previously confused TeaCache's fixed threshold. This triggered aggressive caching on the very first step, resulting in fast generations but heavily distorted images covered in artifacts.
The Solution: We implemented dynamic timestep scale auto-detection st.max_t. TeaCache now mathematically adapts to any sampler and scheduler (sigmas, 1000..0, or 1..0). Early structural steps are fully protected, while late-stage detailing is safely cached. Enjoy perfect image quality with SDE samplers!
2. 💎 Safe One-Click JIT Compilation torch.compile)
Unstable AnimaTorchCompile node removed: The complex external compilation node was prone to PyTorch crashes (CUDA Graphs tensor overwrite errors) when handling dynamic latent dimensions.
Integrated JIT Toggle: We integrated a safe, one-click torch_compile toggle directly into Anima Booster Loader and Checkpoint Loade. It runs on the stable inductor backend (default mode) without CUDA Graphs. Enjoy the same **+20% to +40% speed boost** with **100% stability**!
3. 🗑️ Codebase Cleanup
*Removed AnimaSparseAttention: Local sparse attention on blocks trained on Full Attention destroyed global image geometry and caused structural artifacts.
Removed AnimaTorchCompile: Replaced by the native, stable JIT toggle in the model loaders.
The package is now cleaner, lighter, and completely safe.
4. 📦 Graceful Degradation & Portable Windows Support
All high-performance modules (like SageAttention) are now fully optional. If not installed, the loader will seamlessly fall back to PyTorch's native SDPA without throwing import errors.
Windows/Portable Tip: We recommend installing the ComfyUI-Sage-EasyInstall node via ComfyUI Manager to easily fetch precompiled Triton and SageAttention binary wheels.
🎛️ Recommended Settings for Maximum Speed & Quality:
Anima Booster Loader: Set sage_attention to auto and enable torch_compile. (Note: The first 2-3 generations will have a warm-up phase while PyTorch compiles the blocks).
Anima TeaCache: Set threshold to 0.15 and keep adaptive ON.
For SDE Samplers (like er_sde): Now fully compatible and artifact-free! If you want to push the speed further while maintaining great quality, try raising the TeaCache threshold to 0.22 - 0.25.