Tune a low-memory workflow one load factor at a time
Establish the runnable range of a particular setup, not a universal minimum-VRAM claim derived from a model name.
Purpose and scope
Establish the runnable range of a particular setup, not a universal minimum-VRAM claim derived from a model name.
Source-supported context
Official troubleshooting recommends workload-specific changes to dimensions and batches. PyTorch cache and MPS-limit documentation explain why clearing cache or removing limits has important boundaries. Source 1 Source 2 Source 3
Before you start
1. Record model pairing, precision, GPU/unified memory, system RAM and software versions.
2. Distinguish single-image, batch and video tasks with exact dimensions and frame count.
3. Do not mislabel pressure transferred to RAM by offload as a GPU-only issue.
Steps and checks
The sequence below is an editorial procedure based on the cited context, not a diagnosis already confirmed for your environment.
Step 1. Start with one task. If the workflow and model support it, use batch one and a smaller image or shorter clip; complete load, sampling, decode and save.
Step 2. Increase one supported dimension, duration or model branch at a time and note the failing stage without simultaneously changing sampler, CFG and precision.
Step 3. Address sampling and decoding OOM separately. Use only model/node-supported quantization or tiling and recheck quality and memory.
Step 4. Preserve successful settings and the failure boundary alongside the original workflow. Report success for that configuration rather than a model-wide minimum requirement.
Completion check
Input, versions, memory conditions and complete output form a reproducible record. An isolated success is not a general guarantee.
Limitations and cautions
This pack contains no GPU benchmarks. Precision, offload and tiling can affect speed and output; disabling safeguards is not a substitute for system-memory headroom.
Original sources
- ComfyUI troubleshooting overview — original record checked 2026-09-21.
- torch.cuda.memory.empty_cache — original record checked 2026-09-21.
- MPS environment variables — original record checked 2026-09-21.
Localization prepared: 2026-09-22. The source-check dates above were inherited from the existing article; this translation does not claim they were all rechecked today. No GPU run, minimum-memory measurement or runtime guarantee is supplied.
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Sources & references
Localized from the existing Chinese research draft. Original source-check dates are retained; this translation is not new technical verification or a runtime test.
01ComfyUI troubleshooting overviewSource checked: 2026-09-2102torch.cuda.memory.empty_cacheSource checked: 2026-09-2103MPS environment variablesSource checked: 2026-09-21