The GPT-6 tier chart—what regular folks really need to remember isn’t “the higher, the better.” It’s this: The more complex the task, the more it’s worth letting the model think harder. If it’s just casual Q&A, simple copy edits, or looking something up, Low is enough—fast, lightweight, and cost-effective. For everyday development, plan analysis, product requirements, or generating documents, Medium feels more like the go-to tier, offering a good balance of speed and quality. When it comes to complex code, bug fixing, system design, or deep analysis, that’s when you can move up to High. As for XHigh/Max, they’re better suited for project architecture, complex algorithms, cross-file code, research tasks, or long workflows where “one wrong step can derail everything.” But here’s a common misconception: Higher tiers don’t always mean better answers. For simple questions, making it think too long might actually lead to overcomplication. For clear tasks, the key isn’t the reasoning tier but whether your instructions are clear enough. Here’s how I personally use it: Everyday small tasks: Low Main work: Medium Complex tasks: High Critical projects: XHigh/Max Final review: Use the highest tier sparingly To put it simply, AI isn’t powerful just because you run it at full capacity all the time. The real skill lies in knowing when to save, when to boost, and when to let it think deeply. The biggest change with models like GPT-6 isn’t just that they’re smarter, but that they lower the barrier for “regular people managing complex tasks.” In the future, the gap might not be about who can ask a good prompt, but about who’s better at breaking down tasks, setting standards, controlling costs, and verifying results.