Image and video generation
Before buying a GPU for ComfyUI, choose the image you need to make
You download the model behind an impressive example, but your result looks different. Retries, edits and upscaling soon make the advertised generation time feel irrelevant. Choose hardware around reaching one usable result, not merely the first image.
A background and a product edit are different jobs
Define the result instead of searching for one model that does everything. A background, consistent character scenes and a partial photo edit have different needs. Adding every control and upscaler at once makes failures hard to diagnose. Start with a basic workflow suited to the task and add only the edits you need. Matching one model file does not reproduce an example by itself; check the accompanying encoders, decoders, files and nodes.
Do not raise resolution and batch size together
Once the basic setup works, vary one item at a time. Raising resolution, batch size and control models together makes memory failures difficult to explain. Save a working baseline and change it gradually within the workflow's recommended range; not every model behaves well at arbitrary small resolutions. Check that restoring the baseline also restores operation. Hardware comparisons need matching files and workload settings before their numbers are meaningful.
Upscaling is another stage, not a free finish
Selecting a composition before the final upscale can avoid repeatedly producing large unwanted outputs. Upscaling is still additional work, with its own models or tiled processing and resource needs. Checking whether faces or lettering changed also takes time. Do not read a base-generation benchmark as the delivery time for a finished image. Complete the intended output size and editing process once before judging whether a device can handle your workload.
A matching seed is only part of a fair comparison
Fixing the seed helps, but also record the model, sampler, steps, resolution and software version. Do not assume pixel-identical output across environments. The goal is comparable visual work and cost. Separate initial loading from subsequent generation too. Queuing many images feels different from editing between individual images; knowing which routine you follow clarifies whether throughput or the wait for the next result matters more.
Base the purchase on a saved workflow
Save the working workflow and model filenames once you reach a useful result. You can then ask about performance for your configuration rather than somebody else's few seconds. Treat custom nodes as executable code and assess their source before installing. Use the site's preview to explore estimated waiting differences, and test output quality with the actual model. A faster GPU alone will not fix a prompt or workflow problem. If quality is already satisfactory and repeated waiting is the problem, that time becomes a concrete upgrade rationale.