Expired50% confidenceSolutionExact time
ComfyUI-INT4-Fast supports native mixed-precision checkpoints, determining the compute path at per-layer granularity: backbone modules are routed to INT4 Tensor Cores, while sensitive layers (patch projection) are directed to Triton's INT8 execution path in INT8 format.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/12/2026
First Seen
Valid until: 10/10/2026(expired)
Sources
ComfyUI-INT4-Fast：6GB显卡流畅运行Flux大模型实测
redditr/StableDiffusion7/10/2026
Related Claims
UnverifiedComfyUI-INT4-Fast was independently improved upon BobJohnson24's ComfyUI-INT8-Fast, and relies on comfy-kitchen under the hood to invoke the GPU's Tensor Cores.75% similarUnverifiedThe node employs a per-layer dynamic routing mechanism: backbone modules are routed to INT4 Tensor Core execution, while sensitive layers (patch projection layers) are stored in INT8 format and directed to Triton's INT8 execution path.73% similarUnverifiedTensorRT supports multiple precision calibrations including FP32, FP16, INT8, and FP872% similarUnverifiedThe RTX 6000 Ada's fourth-generation Tensor Cores support FP8 precision computation.69% similarUnverifiedTensorRT-LLM has built-in end-to-end support for quantization formats such as NVFP4, including automatic unpacking of quantized weights, mixed-precision inference scheduling, and operator fusion optimization69% similar
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