Low‑VRAM AI on Windows guide: dynamic VRAM management with ComfyUI
Configure ComfyUI to use dynamic VRAM management on Windows with shared video memory, avoid Linux NVIDIA due to lack of shared memory, and use AMD ROCm GTT memory if on AMD. Test models like SDXL, Illustrious XL, Z‑Image Turbo FP16/FP8 on a GTX 1060 6 GB to confirm performance.
Configure ComfyUI to use dynamic VRAM management on Windows with shared video memory, avoid Linux NVIDIA due to lack of shared memory, and use AMD ROCm GTT memory if on AMD. Test models like SDXL, Illustrious XL, Z‑Image Turbo FP16/FP8 on a GTX 1060 6 GB to confirm performance.
Summary
ComfyUI’s dynamic VRAM management allows low‑VRAM Windows GPUs to run large diffusion models that would otherwise exceed memory limits. The guide explains that Windows’ WDDM driver provides shared video memory, letting the system RAM act as a VRAM extension, while Linux NVIDIA drivers lack this feature and can crash with hard OOM errors. AMD GPUs on Linux can use GTT memory up to 50 % of system RAM, but stability issues and CUDA‑only plugins limit practicality. The author demonstrates that SDXL, Illustrious XL, and Z‑Image Turbo FP16/FP8 can all run on a GTX 1060 6 GB when using ComfyUI’s dynamic loading, whereas batch generation is impractical on 6 GB. The guide also notes that the dynamic VRAM technique relies heavily on Windows shared memory and may not work on Linux or macOS. Users are advised to test models on their hardware and to use the provided benchmark table for reference.
Key changes
- Windows WDDM provides shared video memory for VRAM extension
- Linux NVIDIA lacks shared memory, causing hard OOM crashes
- AMD GTT memory up to 50 % of system RAM, but with stability issues
- ComfyUI dynamic VRAM loads only needed components
- SDXL, Illustrious XL, and Z‑Image Turbo FP16/FP8 run on GTX 1060 6 GB
- Batch generation impractical on 6 GB VRAM
- Dynamic VRAM relies on Windows shared memory; may not work on Linux/macOS
- Benchmark table provided for performance reference