project migration task, GLM-5 demonstrated remarkable autonomy. Tasked with generating database models, migrations, factories, and seeders, the model processed six sub-phases without hand-holding. While it took 23 minutes to complete—significantly longer than Sonnet's 10 minutes—the output explained the delay. GLM-5 didn't just meet the requirements; it over-delivered by creating robust helper methods, scope methods, and granular factory states that the other models ignored.
produced functional but bare-bones code. In contrast, GLM-5 generated 150 lines for a factory file compared to Opus's 97. It included sophisticated testing data points like "approved," "pending," and "rejected" listings, which are essential for realistic project testing. While Opus remains the master of
enums, GLM-5’s inclusion of helper methods like is_active() and record_impression() makes the code immediately more useful for production environments.
The Verdict: Performance vs. Price
The financial argument for GLM-5 is nearly impossible to ignore. Operating through
, the model delivers performance comparable to Opus at roughly one-tenth the cost. For developers managing long-running, complex architectural tasks, the trade-off of slower execution speed for significantly deeper code logic is a winning bargain. Sonnet lost this specific battle by being too concise; GLM-5 won by understanding the future needs of the application.
