Definitely fast, but initial use puts quality either comparable to or below gpt-5-nano. This might be a low-cost option for people who don't mind babysitting the output (or working in very small projects), but claude/gpt-5/gemini all seem to have significantly higher quality at marginally more cost/time.
By just emphasizing the speed here, I wonder if their workflows revolve more around the vibe practice of generating N solutions to a problem in parallel and selecting the "best". If so, it might still win out on speed (if it can reliably produce at least one higher-quality output, which remains to be seen), but also quickly loses any cost margin benefits.
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