Running the 14B BitDance Model Locally Low Vram: Created Custom ComfyUI Nodes

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Running massive 14-billion parameter models locally often results in immediate Out of Memory (OOM) crashes on standard consumer GPUs. This is a summarized guide. For the full JSON workflow and download files, check the original article on my site.

The Architecture Problem

Unlike older models that denoise standard vector systems, BitDance builds images token-by-token using a massive Binary Tokenizer capable of holding 2^256 states. Because it leverages a 14B language model, the text encoding phase is exceptionally heavy. This causes a massive VRAM spike that instantly crashes most hardware.

The Solution: FP8 Conversion & Dynamic Offloading

To bypass these memory limits, I built a custom ComfyUI node suite and converted the model weights to FP8. This significantly reduces the memory footprint while maintaining near-full visual fidelity.

Read the full guide and get the workflow here: https://aistudynow.com/how-to-fix-the-generic-face-bug-in-bitdance-14b-optimize-speed/