Start with the problem in front of you.

Do not infer minimum VRAM from the 7B label. Inspect component residency, cache, reference dimensions and output workload.

Preserve old and new component sets, nodes, adapters and licenses instead of copying commands across runtimes.

The last line of a screenshot rarely identifies the instance, input and first exception. Preserve a complete local record and share a deliberate redacted report.

The backend found a missing required input before execution. Use the reported node and field to repair that specific gap before investigating further failures.

Identify the shell, interpreter and working directory before copying an installation command.

This error can mean a CPU-only Torch build was installed, but it can also come from a node calling CUDA where the selected build or backend cannot provide it.

Completed sampling still leaves latent data that must be decoded into pixels. A VAE failure after sampling therefore differs from memory exhaustion at the start of sampling.

An extraction, Git checkout or node build can fail because of one long path. Identify the failing tool before changing system policy or relocating an existing Python environment.

This Windows error concerns committed system memory. It should not be treated as VRAM exhaustion or proof that a safetensors file is corrupt merely because it appears during model loading.

pip can show xFormers as installed while its C++/CUDA extension fails to load or no attention operator supports the input. Package presence and usable GPU kernels are separate checks.