I put GLM 5.2, the open-weight coding model from Z.AI, through four real tasks inside my actual codebase: a codebase architecture audit, a UI redesign, and a 45-minute autonomous bug-hunting session pulling from Sentry and Vercel logs. Total cost: $3.36 for roughly 6 million tokens, a prioritized bug-fix dashboard I’m actually shipping from, and a landing page redesign that matched Chat PRD’s design system on the first try.
Listen or watch on YouTube, Spotify, or Apple Podcasts
What you’ll learn:
What “open-weight” actually means and why it matters for cost and vendor independence
How to connect GLM 5.2 to Cursor and Claude Code
How it performs on codebase exploration and autonomous architecture summarization in a real production Next.js app
Whether GLM 5.2 can match an existing design system
How the model handles a 45-minute long-running autonomous task
Where GLM 5.2 stumbled
The actual cost breakdown
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In this episode, we cover:
([00:00](https://www.youtube.com/watch?v=ZoBfQZ5utQk)) What open-weight models are and why GLM 5.2 is worth testing
([01:38](https://www.youtube.com/watch?v=ZoBfQZ5utQk&t=98s)) GLM 5.2 model overview
([04:02](https://www.youtube.com/watch?v=ZoBfQZ5utQk&t=242s)) Capabilities and benchmark results
([06:02](https://www.youtube.com/watch?v=ZoBfQZ5utQk&t=362s)) How to set up GLM 5.2 in Cursor
([08:37](https://www.youtube.com/watch?v=ZoBfQZ5utQk&t=517s)) How to set up GLM 5.2 in Claude Code
([11:04](https://www.youtube.com/watch?v=ZoBfQZ5utQk&t=664s)) Live test 1: codebase exploration and architecture audit on ChatPRD
([12:43](https://www.youtube.com/watch?v=ZoBfQZ5utQk&t=763s)) Live test 2: generating an HTML architecture and roadmap page
([16:37](https://www.youtube.com/watch?v=ZoBfQZ5utQk&t=997s)) Live test 3: redesigning the How I AI landing page in Cursor
([20:57](https://www.youtube.com/watch?v=ZoBfQZ5utQk&t=1257s)) Live test 4: 45-minute autonomous task, pulling Sentry errors and Vercel logs
([22:35](https://www.youtube.com/watch?v=ZoBfQZ5utQk&t=1355s)) Where it struggled
([23:49](https://www.youtube.com/watch?v=ZoBfQZ5utQk&t=1429s)) My verdict on the output
([25:23](https://www.youtube.com/watch?v=ZoBfQZ5utQk&t=1523s)) Cost breakdown
Tools referenced:
z.ai:
[https://z.ai](https://z.ai)GLM 5.2:
[https://z.ai/blog/glm-5.2](https://z.ai/blog/glm-5.2)OpenRouter:
[https://openrouter.ai](https://openrouter.ai)Cursor:
[https://cursor.com](https://cursor.com)Claude Code:
[https://docs.anthropic.com/en/docs/claude-code](https://docs.anthropic.com/en/docs/claude-code)Sentry:
[https://sentry.io](https://sentry.io)Vercel:
[https://vercel.com](https://vercel.com)
Other references:
SWE-Bench Pro leaderboard (coding benchmark scores referenced in episode):
[https://www.swebench.com](https://www.swebench.com)Frontier Suite and Post-Train Bench (additional benchmarks cited):
[https://scale.com/leaderboard](https://scale.com/leaderboard)Use Claude Code with OpenRouter:
[https://openrouter.ai/docs/cookbook/coding-agents/claude-code-integration](https://openrouter.ai/docs/cookbook/coding-agents/claude-code-integration)
Where to find Claire Vo:
ChatPRD: [https://www.chatprd.ai/](https://www.chatprd.ai/)
Website: [https://clairevo.com/](https://clairevo.com/)
LinkedIn: [https://www.linkedin.com/in/clairevo/](https://www.linkedin.com/in/clairevo/)
Production and marketing by [https://penname.co/](https://penname.co/). For inquiries about sponsoring the podcast, email [[email protected]](/cdn-cgi/l/email-protection).