Enabling Modern AI Inference on 8 GB GPUs via Hierarchical Offload and Windows Commit Tuning: A ComfyUI Case Study

Modern AI models for image and video generation frequently exceed the VRAM budget available in consumer GPUs (8–12 GB), causing failures that users often interpret as a strict “hardware limit.” This work presents a reproducible case study in which recurring errors (including GPU “out of memory” and Windows OS error 1455) were mitigated through (i) VRAM policy tuning (LOW_VRAM) in the ComfyUI runtime, (ii) explicit asynchronous offload configuration and pinned memory disabling, and (iii) increasing the Windows commit limit via the paging file (pagefile) on NVMe storage. With these changes, it was possible to run Full HD (1080p) video-generation workloads on a mobile RTX 4070 8 GB (laptop) GPU in a repeatable manner. In addition, practical limits (e.g., 2K+) and risks are documented, including system stability failures (BSOD CLOCK_WATCHDOG_TIMEOUT) under stress regimes.