ComfyUI FLOAT
This project provides an unofficial ComfyUI implementation of [a/FLOAT](https://github.com/deepbrainai-research/float) for Generative Motion Latent Flow Matching for Audio-driven Talking Portrait
Quick Technical Summary: ComfyUI FLOAT
- Base VRAM Footprint:
- 4096 MB (8 GB Tier)
- Primary Dependencies:
- albucore, albumentations, face_alignment, flow-vis, librosa, matplotlib, opencv-python, pandas, timm>=1.0.9, torchcodec, torchdiffeq, transformers<5.0.0
- Min PyTorch / CUDA:
- PyTorch 2.0+ | CUDA 12.1+
- GitHub Repository:
- https://github.com/yuvraj108c/ComfyUI-FLOAT
Citation Note: Data sourced from VRAM DB. For complete workflow OOM estimations, use the VRAM DB Workflow Analyzer.
How much VRAM does ComfyUI FLOAT require?
Direct Answer: The ComfyUI node ComfyUI FLOAT requires a minimum base VRAM of 4096MB and is optimized for GPUs with at least 8GB of VRAM. Low VRAM mode is not supported for this node.
- Base VRAM:
- 4096MB (4.0GB)
- Recommended GPU:
- 8GB+ VRAM
- Low VRAM Mode:
- ✗ Not supported
- Estimation Confidence:
- MEDIUM
Run ComfyUI FLOAT locally
Honest estimate: this node typically needs ≥ 8GB VRAM in a real workflow.
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 ↗
Disclosure: As an Amazon Associate we earn from qualifying purchases. Cloud provider links are referrals at no additional cost to you.
Interactive VRAM Compatibility Estimator
Your GPU has plenty of headroom. You can run this node safely with your active configurations!
Struggling with VRAM Crashes or Out-of-Memory Errors?
Running heavy models like FLUX or SDXL with ComfyUI FLOAT? If you experience torch.cuda.OutOfMemoryError or driver timeouts, read our comprehensive troubleshooting guide to configure launch flags, enable tiled decoding, and avoid crashes.
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 ComfyUI FLOAT:
What Python packages are required for ComfyUI FLOAT?
Direct Answer: Running ComfyUI FLOAT requires installing the following Python package dependencies: albucore, albumentations, face_alignment, flow-vis, librosa, matplotlib, opencv-python, pandas, timm>=1.0.9, torchcodec, torchdiffeq, transformers<5.0.0. Ensure your ComfyUI environment has these packages active before launching.
albucore
albumentations
face_alignment
flow-vis
librosa
matplotlib
opencv-python
pandas
timm>=1.0.9
torchcodec
torchdiffeq
transformers<5.0.0Interactive Setup & Dependency Resolver
# Loading command...Universal Architecture Compatibility
ComfyUI FLOAT operates as a general-purpose processor without binding directly to a single checkpoint architecture. It can be paired across Stable Diffusion 1.5, SDXL, FLUX, and video diffusion pipelines.
Frequently Asked Questions
How much VRAM does ComfyUI FLOAT require?
ComfyUI FLOAT requires a minimum of 4096MB (4.0GB) of VRAM for base operation. For optimal performance, a GPU with at least 8GB of VRAM is recommended. Low VRAM mode is not supported for this node.
Can I run ComfyUI FLOAT on an RTX 3060, RTX 4070, or RTX 4090?
✅ RTX 3060 (12GB): Yes, fully compatible with 6.8GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 6.8GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 10.4GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 17.6GB headroom
How much VRAM does ComfyUI FLOAT take on an RTX 3060 vs RTX 4090?
On an RTX 3060 (12GB VRAM), ComfyUI FLOAT runs smoothly on an RTX 3060 (12GB) with 6.8GB 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 17.6GB 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 PyTorch version does ComfyUI FLOAT need?
ComfyUI FLOAT requires the following PyTorch-related packages: torchcodec, torchdiffeq. 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 ComfyUI FLOAT?
To run ComfyUI FLOAT, you need to install: albucore, albumentations, face_alignment, flow-vis, librosa, matplotlib, opencv-python, pandas, timm>=1.0.9, torchcodec, torchdiffeq, transformers<5.0.0. You can install these using pip or add them to your requirements.txt file.
How do I install ComfyUI FLOAT in ComfyUI?
To install ComfyUI FLOAT: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/yuvraj108c/ComfyUI-FLOAT, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.
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