Adobe Photoshop AI Credits: Which Tools Drain Your Balance Fast

AI in Photoshop and Lightroom now comes with a meter running in the background, and it is easy to burn through credits without realizing which button did it. If you shoot and edit photos for clients or personal work, that uncertainty can change how you plan edits, what you try first, and what you avoid touching at all.

Coming to you from Aaron Nace with Phlearn, this practical video lays out a simple rule you can use to predict credit use before you click: if a tool creates brand-new pixels, expect credits, and if it only analyzes what is already there, expect none. That sounds clean until you hit real workflows, where you bounce between selection, masking, blur, cleanup, and generative tools in the same session. The video walks through the zero-credit side first, starting with AI-powered selections like Select Subject and Remove Background, then expanding to tools that can target specific people or parts of a person. It also points out that similar AI masking exists in Adobe Camera Raw and Lightroom, and it behaves the same way in terms of credits. If you have been avoiding these features because “AI equals credits,” this part alone can change how you start most edits.

The second half gets more tactical, because it moves into the actions that actually drain your balance, and the costs are not always intuitive. Generative Expand is presented as a border-growth tool that feels harmless until you generate, then you get multiple variations and each one counts against your monthly pool. Generative Fill is shown in the common “remove something” use case, where leaving the prompt blank tells Photoshop to erase the selected object, but it still produces several options and you pay for each. The detail that matters is choice architecture: some tools default to three variations, while others can produce a single result, and the difference shows up in credits even when the edit goal is identical. That leads into a comparison that you should not skip if you do frequent cleanup, because it can save credits on every job while still keeping a high success rate.

A key segment focuses on the Remove tool, because it can behave like two different tools depending on a small setting. With generative AI turned off, it relies on classic content-aware approaches, which can be acceptable on simple textures but can also repeat patterns and soften detail in ways that look wrong at normal viewing sizes. Flip generative AI on, and the output improves, but the credit hit changes too, and the video highlights that it can be cheaper than Generative Fill for the same removal because it may generate only one result instead of three. You also get a workflow tip that is easy to adopt: start with the no-credit version, then escalate only if you see obvious artifacts, while keeping the result on a new layer so you can compare and mask. That single habit can reduce waste without turning you into someone who second-guesses every click.

Where the video gets tense is in the section on adding objects, because the cost-to-quality ratio can swing wildly. You see a real example of trying to add a rabbit, starting with Adobe’s own Firefly model, then moving to partner models, and the credit prices jump fast while the output still might not blend well. The video shows where Photoshop hides the per-generation credit cost for each model, so you can check before you commit, and you see why that matters when one model can be 10 credits for a single attempt and another can be 20 or 40. You also get a sober reminder that credits reset monthly and do not roll over, and that you cannot “undo” the spend even if the result is unusable. There is also a quick walkthrough of how to check your balance in your Adobe account, using a real starting number and a real end number from the session, which makes the tradeoffs feel less abstract. The most useful takeaway is not “never use premium models,” but knowing when you are gambling on an insert that may not match lighting, focus, and grain, even if the subject looks decent. Check out the video above for the full rundown from Nace.