ComfyUI_StreamingT2V
ComfyUI_StreamingT2V
Quick Technical Summary: ComfyUI_StreamingT2V
- Base VRAM Footprint:
- 128 MB (4 GB Tier)
- Primary Dependencies:
- accelerate, addict, albumentations, av, bitsandbytes, boto3, clip@ git+https://github.com/openai/CLIP.git@a1d071733d7111c9c014f024669f959182114e33, datasets, decord, diffusers, easydict, einops, fairscale, ffmpeg, gast, gdown, huggingface-hub, imageio, ipython, jsonargparse>=4.26.1, omegaconf, open-clip-torch, oss2, pandas, pibble, pytorch-lightning, raft, rich, rotary-embedding-torch, scikit-image, scikit-learn, scipy, seaborn, simplejson, sortedcontainers, torchsde, tqdm, transformers, xformers, yapf
- Min PyTorch / CUDA:
- PyTorch 2.0+ | CUDA 12.1+
- GitHub Repository:
- https://github.com/chaojie/ComfyUI_StreamingT2V
Citation Note: Data sourced from VRAM DB. For complete workflow OOM estimations, use the VRAM DB Workflow Analyzer.
How much VRAM does ComfyUI_StreamingT2V require?
Direct Answer: The ComfyUI node ComfyUI_StreamingT2V requires a minimum base VRAM of 128MB and is optimized for GPUs with at least 4GB of VRAM. Low VRAM mode is fully supported for resource-constrained setups.
- Base VRAM:
- 128MB (0.1GB)
- Recommended GPU:
- 4GB+ VRAM
- Low VRAM Mode:
- ✓ Supported
- Estimation Confidence:
- MEDIUM
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 ComfyUI_StreamingT2V:
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.
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What Python packages are required for ComfyUI_StreamingT2V?
Direct Answer: Running ComfyUI_StreamingT2V requires installing the following Python package dependencies: accelerate, addict, albumentations, av, bitsandbytes, boto3, clip@ git+https://github.com/openai/CLIP.git@a1d071733d7111c9c014f024669f959182114e33, datasets, decord, diffusers, easydict, einops, fairscale, ffmpeg, gast, gdown, huggingface-hub, imageio, ipython, jsonargparse>=4.26.1, omegaconf, open-clip-torch, oss2, pandas, pibble, pytorch-lightning, raft, rich, rotary-embedding-torch, scikit-image, scikit-learn, scipy, seaborn, simplejson, sortedcontainers, torchsde, tqdm, transformers, xformers, yapf. Ensure your ComfyUI environment has these packages active before launching.
accelerate
addict
albumentations
av
bitsandbytes
boto3
clip@ git+https://github.com/openai/CLIP.git@a1d071733d7111c9c014f024669f959182114e33
datasets
decord
diffusers
easydict
einops
fairscale
ffmpeg
gast
gdown
huggingface-hub
imageio
ipython
jsonargparse>=4.26.1
omegaconf
open-clip-torch
oss2
pandas
pibble
pytorch-lightning
raft
rich
rotary-embedding-torch
scikit-image
scikit-learn
scipy
seaborn
simplejson
sortedcontainers
torchsde
tqdm
transformers
xformers
yapfInteractive Setup & Dependency Resolver
# Loading command...Frequently Asked Questions
How much VRAM does ComfyUI_StreamingT2V require?
ComfyUI_StreamingT2V requires a minimum of 128MB (0.1GB) 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 ComfyUI_StreamingT2V on an RTX 3060, RTX 4070, or RTX 4090?
✅ RTX 3060 (12GB): Yes, fully compatible with 10.7GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 10.7GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 14.3GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 21.5GB headroom
How much VRAM does ComfyUI_StreamingT2V take on an RTX 3060 vs RTX 4090?
On an RTX 3060 (12GB VRAM), ComfyUI_StreamingT2V runs smoothly on an RTX 3060 (12GB) with 10.7GB 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 21.5GB 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_StreamingT2V need?
ComfyUI_StreamingT2V requires the following PyTorch-related packages: open-clip-torch, pytorch-lightning, rotary-embedding-torch, torchsde. 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_StreamingT2V?
To run ComfyUI_StreamingT2V, you need to install: accelerate, addict, albumentations, av, bitsandbytes, boto3, clip@ git+https://github.com/openai/CLIP.git@a1d071733d7111c9c014f024669f959182114e33, datasets, decord, diffusers, easydict, einops, fairscale, ffmpeg, gast, gdown, huggingface-hub, imageio, ipython, jsonargparse>=4.26.1, omegaconf, open-clip-torch, oss2, pandas, pibble, pytorch-lightning, raft, rich, rotary-embedding-torch, scikit-image, scikit-learn, scipy, seaborn, simplejson, sortedcontainers, torchsde, tqdm, transformers, xformers, yapf. You can install these using pip or add them to your requirements.txt file.
How can I reduce VRAM usage when running ComfyUI_StreamingT2V?
ComfyUI_StreamingT2V 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 ComfyUI_StreamingT2V in ComfyUI?
To install ComfyUI_StreamingT2V: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/chaojie/ComfyUI_StreamingT2V, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.