Token efficiency is the sleeper metric in AI coding tools. Raw benchmark scores look good in press releases. Token burn shows up in your bill.
A writer at XDA ran Grok 4.5 through a real-world project inside Cursor: build a polished premium sneakers website from scratch, with a detailed prompt covering layout, navigation, product descriptions, and visual style. Grok 4.5 completed the project using roughly 40k tokens total. The writer noted the site looked usable immediately, not like a generic AI-generated storefront that needed rebuilding.
What stood out
- Speed and direction: The model understood the project structure quickly and moved through it without prolonged planning phases that burn context before producing anything.
- Focused edits: On follow-up tweaks (spacing, text changes, UI fixes), Grok 4.5 identified the relevant file, made the change, and moved on. It did not re-read unrelated files or generate lengthy plans before touching a few lines of code.
- Token economy: The writer’s take is that near-equivalent output at lower token cost is a worthwhile trade, even if the model does not beat OpenAI or Anthropic on raw capability.
Where it falls short
The writer still switches to other models for complicated features, messy codebases, or problems that need deeper reasoning before touching code. Grok 4.5 is not a universal replacement.
Grok 4.6 is expected soon. The writer hopes it keeps the efficiency while handling complex tasks better.
For solo builders doing rapid iteration in Cursor, the token story alone is worth a test run.
