XB_ToolBox
A comprehensive ComfyUI extension suite encompassing both front-end interaction and low-level memory scheduling, designed to help beginners master workflows and simplify local deployment.
Quick Technical Summary: XB_ToolBox
- Base VRAM Footprint:
- 256 MB (4 GB Tier)
- Primary Dependencies:
- aiohttp# 异步HTTP (音频波形端点), av# PyAV - 音频解码 (AudioSlicer), conformer>=0.3.2 # Conformer 模型组件, diffusers>=0.29.0 # Diffusers 扩散模型, diskcache# 磁盘缓存, easyocr# OCR 文字识别 (漫画工具), einops# 张量操作, gguf# GGUF 模型格式解析, huggingface_hub# HuggingFace 模型下载, hydra-core>=1.3.0 # Hydra 配置框架, hyperpyyaml>=1.2.0 # YAML 配置解析, imageio-ffmpeg# FFmpeg 回退 (视频服务器), inflect>=7.0.0 # 英文单词变形, librosa>=0.10.0 # 音频处理, matplotlib# 可视化 (训练/绘图), modelscope# ModelScope 模型下载, numpy, omegaconf>=2.3.0 # OmegaConf 配置, onnxruntime>=1.18.0 # ONNX 推理 (人像分割 + CosyVoice3), openai-whisper# 语音转文字 (自动转录), opencv-python# 图像处理 (漫画/视频节点), pillow, psutil# CPU/内存/磁盘系统信息, pyarrow>=14.0.0 # Arrow 数据处理, pydantic>=2.0.0 # 数据验证, pythonnet# .NET 桥接 (LibreHardwareMonitor GPU 监控), pyworld>=0.3.0 # 基频提取 (WORLD vocoder), regex# 高级正则表达式, requests# HTTP 请求, ruamel.yaml<0.18 # YAML 读写, scipy# 科学计算, soundfile>=0.12.0 # 音频文件读写, tiktoken# BPE 分词器, tqdm, transformers>=4.40.0 # 模型/分词器, wetext>=0.1.0 # 文本规范化, x-transformers>=2.0.0 # Transformer 扩展
- Min PyTorch / CUDA:
- PyTorch 2.0+ | CUDA 12.1+
- GitHub Repository:
- https://github.com/WJLUOXIAO/XB_ToolBox
Citation Note: Data sourced from VRAM DB. For complete workflow OOM estimations, use the VRAM DB Workflow Analyzer.
How much VRAM does XB_ToolBox require?
Direct Answer: The ComfyUI node XB_ToolBox requires a minimum base VRAM of 256MB and is optimized for GPUs with at least 4GB of VRAM. Low VRAM mode is fully supported for resource-constrained setups.
- Base VRAM:
- 256MB (0.3GB)
- Recommended GPU:
- 4GB+ VRAM
- Low VRAM Mode:
- ✓ Supported
- Estimation Confidence:
- HIGH
Cheapest VRAM Upgrade Paths (Live Market Prices):
- GeForce RTX 3060 12GB (Ultimate Budget VRAM King)──► Used: $209.62View eBay ↗
- GeForce RTX 4060 8GB (Modern Entry-Level)──► New: $303.50View Amazon ↗
Interactive VRAM Compatibility Estimator
Your GPU has plenty of headroom. You can run this node safely with your active configurations!
Verify Compatibility for Your Specific GPU VRAM
Select your graphics card's VRAM capacity to view optimized batch sizes, suggested resolutions, and custom performance tips for XB_ToolBox:
Buy NVIDIA GeForce RTX 3060 (12GB VRAM)
Tired of renting cloud rigs? Run ComfyUI locally with absolute zero latency. Best entry-level ComfyUI experience. Avoids immediate VRAM limitations on basic LoRA training.
Are you the author of this node?
Help your users avoid out-of-memory errors by displaying this professional, dynamic VRAM badge on your GitHub README. Copy the markdown below to embed it with a backlink directly to this hardware specification profile.
What Python packages are required for XB_ToolBox?
Direct Answer: Running XB_ToolBox requires installing the following Python package dependencies: aiohttp# 异步HTTP (音频波形端点), av# PyAV - 音频解码 (AudioSlicer), conformer>=0.3.2 # Conformer 模型组件, diffusers>=0.29.0 # Diffusers 扩散模型, diskcache# 磁盘缓存, easyocr# OCR 文字识别 (漫画工具), einops# 张量操作, gguf# GGUF 模型格式解析, huggingface_hub# HuggingFace 模型下载, hydra-core>=1.3.0 # Hydra 配置框架, hyperpyyaml>=1.2.0 # YAML 配置解析, imageio-ffmpeg# FFmpeg 回退 (视频服务器), inflect>=7.0.0 # 英文单词变形, librosa>=0.10.0 # 音频处理, matplotlib# 可视化 (训练/绘图), modelscope# ModelScope 模型下载, numpy, omegaconf>=2.3.0 # OmegaConf 配置, onnxruntime>=1.18.0 # ONNX 推理 (人像分割 + CosyVoice3), openai-whisper# 语音转文字 (自动转录), opencv-python# 图像处理 (漫画/视频节点), pillow, psutil# CPU/内存/磁盘系统信息, pyarrow>=14.0.0 # Arrow 数据处理, pydantic>=2.0.0 # 数据验证, pythonnet# .NET 桥接 (LibreHardwareMonitor GPU 监控), pyworld>=0.3.0 # 基频提取 (WORLD vocoder), regex# 高级正则表达式, requests# HTTP 请求, ruamel.yaml<0.18 # YAML 读写, scipy# 科学计算, soundfile>=0.12.0 # 音频文件读写, tiktoken# BPE 分词器, tqdm, transformers>=4.40.0 # 模型/分词器, wetext>=0.1.0 # 文本规范化, x-transformers>=2.0.0 # Transformer 扩展. Ensure your ComfyUI environment has these packages active before launching.
aiohttp# 异步HTTP (音频波形端点)
av# PyAV - 音频解码 (AudioSlicer)
conformer>=0.3.2 # Conformer 模型组件
diffusers>=0.29.0 # Diffusers 扩散模型
diskcache# 磁盘缓存
easyocr# OCR 文字识别 (漫画工具)
einops# 张量操作
gguf# GGUF 模型格式解析
huggingface_hub# HuggingFace 模型下载
hydra-core>=1.3.0 # Hydra 配置框架
hyperpyyaml>=1.2.0 # YAML 配置解析
imageio-ffmpeg# FFmpeg 回退 (视频服务器)
inflect>=7.0.0 # 英文单词变形
librosa>=0.10.0 # 音频处理
matplotlib# 可视化 (训练/绘图)
modelscope# ModelScope 模型下载
numpy
omegaconf>=2.3.0 # OmegaConf 配置
onnxruntime>=1.18.0 # ONNX 推理 (人像分割 + CosyVoice3)
openai-whisper# 语音转文字 (自动转录)
opencv-python# 图像处理 (漫画/视频节点)
pillow
psutil# CPU/内存/磁盘系统信息
pyarrow>=14.0.0 # Arrow 数据处理
pydantic>=2.0.0 # 数据验证
pythonnet# .NET 桥接 (LibreHardwareMonitor GPU 监控)
pyworld>=0.3.0 # 基频提取 (WORLD vocoder)
regex# 高级正则表达式
requests# HTTP 请求
ruamel.yaml<0.18 # YAML 读写
scipy# 科学计算
soundfile>=0.12.0 # 音频文件读写
tiktoken# BPE 分词器
tqdm
transformers>=4.40.0 # 模型/分词器
wetext>=0.1.0 # 文本规范化
x-transformers>=2.0.0 # Transformer 扩展Interactive Setup & Dependency Resolver
# Loading command...Frequently Asked Questions
How much VRAM does XB_ToolBox require?
XB_ToolBox requires a minimum of 256MB (0.3GB) of VRAM for base operation. For optimal performance, a GPU with at least 4GB of VRAM is recommended. This node supports low VRAM mode for resource-constrained setups.
Can I run XB_ToolBox on an RTX 3060, RTX 4070, or RTX 4090?
✅ RTX 3060 (12GB): Yes, fully compatible with 10.6GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 10.6GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 14.2GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 21.4GB headroom
How much VRAM does XB_ToolBox take on an RTX 3060 vs RTX 4090?
On an RTX 3060 (12GB VRAM), XB_ToolBox runs smoothly on an RTX 3060 (12GB) with 10.6GB of headroom. This is sufficient to run the node alongside standard SD 1.5 and SDXL workflows in full precision. On an RTX 4090 (24GB VRAM), the node runs with extreme headroom on an RTX 4090 (24GB) with 21.4GB of dedicated headroom. This allows you to combine the node with massive models (like FLUX.1 Dev, Schnell, or Hunyuan Video) in full precision (FP16) without any offload flags.
What Python packages are required for XB_ToolBox?
To run XB_ToolBox, you need to install: aiohttp# 异步HTTP (音频波形端点), av# PyAV - 音频解码 (AudioSlicer), conformer>=0.3.2 # Conformer 模型组件, diffusers>=0.29.0 # Diffusers 扩散模型, diskcache# 磁盘缓存, easyocr# OCR 文字识别 (漫画工具), einops# 张量操作, gguf# GGUF 模型格式解析, huggingface_hub# HuggingFace 模型下载, hydra-core>=1.3.0 # Hydra 配置框架, hyperpyyaml>=1.2.0 # YAML 配置解析, imageio-ffmpeg# FFmpeg 回退 (视频服务器), inflect>=7.0.0 # 英文单词变形, librosa>=0.10.0 # 音频处理, matplotlib# 可视化 (训练/绘图), modelscope# ModelScope 模型下载, numpy, omegaconf>=2.3.0 # OmegaConf 配置, onnxruntime>=1.18.0 # ONNX 推理 (人像分割 + CosyVoice3), openai-whisper# 语音转文字 (自动转录), opencv-python# 图像处理 (漫画/视频节点), pillow, psutil# CPU/内存/磁盘系统信息, pyarrow>=14.0.0 # Arrow 数据处理, pydantic>=2.0.0 # 数据验证, pythonnet# .NET 桥接 (LibreHardwareMonitor GPU 监控), pyworld>=0.3.0 # 基频提取 (WORLD vocoder), regex# 高级正则表达式, requests# HTTP 请求, ruamel.yaml<0.18 # YAML 读写, scipy# 科学计算, soundfile>=0.12.0 # 音频文件读写, tiktoken# BPE 分词器, tqdm, transformers>=4.40.0 # 模型/分词器, wetext>=0.1.0 # 文本规范化, x-transformers>=2.0.0 # Transformer 扩展. You can install these using pip or add them to your requirements.txt file.
How can I reduce VRAM usage when running XB_ToolBox?
XB_ToolBox supports low VRAM mode. To reduce memory usage: (1) Enable --lowvram or --medvram flags in ComfyUI, (2) Reduce batch size to 1, (3) Use fp16 or fp8 precision if supported, (4) Close other GPU applications.
How do I install XB_ToolBox in ComfyUI?
To install XB_ToolBox: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/WJLUOXIAO/XB_ToolBox, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.