Sure, but now you get a good gaming GPU that you can write off as a business expense.

Clearly you’re looking at the task through the eyes of a hobbyist or “of the month” project so the workflow and pace may not be obvious but API budgets spend fast. Just look at the benchmarks in this article to see how many tried some of these changes took- 47, there goes $3 in 3 minutes, or half that time if your quick on the keyboard.

And even then! Well, you’re limited aren’t you? Limited to the Gemini model, or OpenAI, or whoever, and you see the limits of any one model in the article as well. Or you plonk down for a mediocre GPU with some slight VRAM headroom and choose from dozens of models, countless Lora, control nets, and other options, infinitely flexible in painting and outpainting. Ahead of that you’ll need to budget at least a dozen hours to learn local genai tools, comfyui or others. Then, for under a $1 dollar in electricity, you can can queue up a dozen ideas overnight and get 1,000 variations on each of them handed to you in the morning to quickly triage over coffee and email catchup.

It’s not a one size fits all market though, and most professionals are likely finding they want both: A low-cost, high-control, high precision sandbox that isn’t as fast or scalable as the api, and the api for when fast and scalable is what you need.