Using GLM 5.2 Fast to deliver one engineer-month in just four days and $218 of tokens

In a recent project, an engineer successfully implemented a complex "reclaim" capability for a GPU scheduler, typically estimated as a month-long task, in just four days using the GLM 5.2 Fast model through FireConnect on Claude Code, at an inference cost of $218. This rapid development was achieved by leveraging the model's ability to quickly iterate through design, planning, and implementation phases, producing 3,000 lines of code with all unit and integration tests passing. The engineer highlighted the model's real-time feedback, which allowed for efficient problem-solving and decision-making without the typical delays associated with AI speeds and monthly token limits, thus enabling a more productive workflow. This experience underscored the transformative potential of fast open models in enhancing senior engineers' efficiency by reducing context-switching and improving focus, ultimately delivering quality results at a fraction of the usual time and cost.

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