IF_LLM
Run Local and API LLMs, Features Conditioning manipulation via Omost, supports Ollama, LlamaCPP LMstudio, Koboldcpp, TextGen, Transformers or via APIs Anthropic, Groq, OpenAI, Google Gemini, Mistral, xAI and create your own charcters assistants (SystemPrompts) with custom presets and muchmore
How much VRAM does IF_LLM require?
Direct Answer: The ComfyUI node IF_LLM 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
Interactive VRAM Compatibility Estimator
Your GPU has plenty of headroom. You can run this node safely with your active configurations!
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Deploy on Cloud GPUs
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What Python packages are required for IF_LLM?
Direct Answer: Running IF_LLM requires installing the following Python package dependencies: accelerate, aiohttp>=3.8.5, anthropic, datasets, decord>=0.6.0, ffmpeg-python>=0.2.0, google-genai, groq, https://github.com/woct0rdho/triton-windows/releases/download/v3.1.0-windows.post8/triton-3.1.0-cp312-cp312-win_amd64.whl; sys_platform == "win64" and (python_version >= "3.12" and python_version < "3.13"), https://github.com/woct0rdho/triton-windows/releases/download/v3.1.0-windows.post8/triton-3.1.0-cp311-cp311-win_amd64.whl; sys_platform == "win64" and (python_version >= "3.11" and python_version < "3.12"), https://github.com/woct0rdho/triton-windows/releases/download/v3.1.0-windows.post8/triton-3.1.0-cp310-cp310-win_amd64.whl; sys_platform == "win64" and (python_version >= "3.10" and python_version < "3.11"), https://github.com/woct0rdho/triton-windows/releases/download/v3.1.0-windows.post8/triton-3.1.0-cp38-cp38-win_amd64.whl; sys_platform == "win64" and (python_version >= "3.8" and python_version < "3.9"), huggingface_hub>=0.26.0, imageio_ffmpeg>=0.6.0, mistralai, moviepy>=2.1.2, numpy>=1.24.0, opencv-python>=4.8.0, packaging>=23.1, pillow>=10.0.0, psutil>=5.9.0, pydantic, python-dotenv, python-slugify>=8.0.1, qwen-vl-utils, requests>=2.31.0, rich, safetensors>=0.3.1, scenedetect>=0.6.2, sentence-transformers, tiktoken, tokenizers>=0.15.0, torch>=2.0.0, tqdm>=4.66.1, transformers>=4.49.0, triton; sys_platform == "linux", yt-dlp>=2023.3.4. This node specifically requires PyTorch version 2.0.0 or newer.
accelerate
aiohttp>=3.8.5
anthropic
datasets
decord>=0.6.0
ffmpeg-python>=0.2.0
google-genai
groq
https://github.com/woct0rdho/triton-windows/releases/download/v3.1.0-windows.post8/triton-3.1.0-cp312-cp312-win_amd64.whl; sys_platform == "win64" and (python_version >= "3.12" and python_version < "3.13")
https://github.com/woct0rdho/triton-windows/releases/download/v3.1.0-windows.post8/triton-3.1.0-cp311-cp311-win_amd64.whl; sys_platform == "win64" and (python_version >= "3.11" and python_version < "3.12")
https://github.com/woct0rdho/triton-windows/releases/download/v3.1.0-windows.post8/triton-3.1.0-cp310-cp310-win_amd64.whl; sys_platform == "win64" and (python_version >= "3.10" and python_version < "3.11")
https://github.com/woct0rdho/triton-windows/releases/download/v3.1.0-windows.post8/triton-3.1.0-cp38-cp38-win_amd64.whl; sys_platform == "win64" and (python_version >= "3.8" and python_version < "3.9")
huggingface_hub>=0.26.0
imageio_ffmpeg>=0.6.0
mistralai
moviepy>=2.1.2
numpy>=1.24.0
opencv-python>=4.8.0
packaging>=23.1
pillow>=10.0.0
psutil>=5.9.0
pydantic
python-dotenv
python-slugify>=8.0.1
qwen-vl-utils
requests>=2.31.0
rich
safetensors>=0.3.1
scenedetect>=0.6.2
sentence-transformers
tiktoken
tokenizers>=0.15.0
torch>=2.0.0
tqdm>=4.66.1
transformers>=4.49.0
triton; sys_platform == "linux"
yt-dlp>=2023.3.4Interactive Setup & Dependency Resolver
# Loading command...Special Environment Requirements:
Requires PyTorch version 2.0.0+.
# Loading PyTorch command...Frequently Asked Questions
How much VRAM does IF_LLM require?
IF_LLM 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 IF_LLM 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
What PyTorch version does IF_LLM need?
IF_LLM requires the following PyTorch-related packages: torch>=2.0.0. Ensure your ComfyUI environment has these installed. Ensure your PyTorch installation matches your CUDA version (use torch.version.cuda to check).
What Python packages are required for IF_LLM?
To run IF_LLM, you need to install: accelerate, aiohttp>=3.8.5, anthropic, datasets, decord>=0.6.0, ffmpeg-python>=0.2.0, google-genai, groq, https://github.com/woct0rdho/triton-windows/releases/download/v3.1.0-windows.post8/triton-3.1.0-cp312-cp312-win_amd64.whl; sys_platform == "win64" and (python_version >= "3.12" and python_version < "3.13"), https://github.com/woct0rdho/triton-windows/releases/download/v3.1.0-windows.post8/triton-3.1.0-cp311-cp311-win_amd64.whl; sys_platform == "win64" and (python_version >= "3.11" and python_version < "3.12"), https://github.com/woct0rdho/triton-windows/releases/download/v3.1.0-windows.post8/triton-3.1.0-cp310-cp310-win_amd64.whl; sys_platform == "win64" and (python_version >= "3.10" and python_version < "3.11"), https://github.com/woct0rdho/triton-windows/releases/download/v3.1.0-windows.post8/triton-3.1.0-cp38-cp38-win_amd64.whl; sys_platform == "win64" and (python_version >= "3.8" and python_version < "3.9"), huggingface_hub>=0.26.0, imageio_ffmpeg>=0.6.0, mistralai, moviepy>=2.1.2, numpy>=1.24.0, opencv-python>=4.8.0, packaging>=23.1, pillow>=10.0.0, psutil>=5.9.0, pydantic, python-dotenv, python-slugify>=8.0.1, qwen-vl-utils, requests>=2.31.0, rich, safetensors>=0.3.1, scenedetect>=0.6.2, sentence-transformers, tiktoken, tokenizers>=0.15.0, torch>=2.0.0, tqdm>=4.66.1, transformers>=4.49.0, triton; sys_platform == "linux", yt-dlp>=2023.3.4. You can install these using pip or add them to your requirements.txt file.
How can I reduce VRAM usage when running IF_LLM?
IF_LLM 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 IF_LLM in ComfyUI?
To install IF_LLM: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/if-ai/ComfyUI-IF_LLM, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.