EPISODE · Jun 24, 2026 · 27 MIN
GLM 5.2: why I’m replacing Opus in Claude Code with this new model
from How I AI · host Claire Vo
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.What you’ll learn:What “open-weight” actually means and why it matters for cost and vendor independenceHow to connect GLM 5.2 to Cursor and Claude CodeHow it performs on codebase exploration and autonomous architecture summarization in a real production Next.js appWhether GLM 5.2 can match an existing design systemHow the model handles a 45-minute long-running autonomous taskWhere GLM 5.2 stumbled The actual cost breakdown—Brought to you by:Mercury—Radically different banking loved by over 300K entrepreneurs—In this episode, we cover:(00:00) What open-weight models are and why GLM 5.2 is worth testing(01:38) GLM 5.2 model overview(04:02) Capabilities and benchmark results(06:02) How to set up GLM 5.2 in Cursor(08:37) How to set up GLM 5.2 in Claude Code(11:04) Live test 1: codebase exploration and architecture audit on ChatPRD(12:43) Live test 2: generating an HTML architecture and roadmap page(16:37) Live test 3: redesigning the How I AI landing page in Cursor(20:57) Live test 4: 45-minute autonomous task, pulling Sentry errors and Vercel logs(22:35) Where it struggled(23:49) My verdict on the output(25:23) Cost breakdown—Tools referenced:z.ai: https://z.aiGLM 5.2: https://z.ai/blog/glm-5.2OpenRouter: https://openrouter.aiCursor: https://cursor.comClaude Code: https://docs.anthropic.com/en/docs/claude-codeSentry: https://sentry.ioVercel: https://vercel.com—Other references:SWE-Bench Pro leaderboard (coding benchmark scores referenced in episode): https://www.swebench.comFrontier Suite and Post-Train Bench (additional benchmarks cited): https://scale.com/leaderboardUse Claude Code with OpenRouter: https://openrouter.ai/docs/cookbook/coding-agents/claude-code-integration—Where to find Claire Vo:ChatPRD: https://www.chatprd.ai/Website: https://clairevo.com/LinkedIn: https://www.linkedin.com/in/clairevo/X: https://x.com/clairevo—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].
What this episode covers
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.What you’ll learn:What “open-weight” actually means and why it matters for cost and vendor independenceHow to connect GLM 5.2 to Cursor and Claude CodeHow it performs on codebase exploration and autonomous architecture summarization in a real production Next.js appWhether GLM 5.2 can match an existing design systemHow the model handles a 45-minute long-running autonomous taskWhere GLM 5.2 stumbled The actual cost breakdown—Brought to you by:Mercury—Radically different banking loved by over 300K entrepreneurs—In this episode, we cover:(00:00) What open-weight models are and why GLM 5.2 is worth testing(01:38) GLM 5.2 model overview(04:02) Capabilities and benchmark results(06:02) How to set up GLM 5.2 in Cursor(08:37) How to set up GLM 5.2 in Claude Code(11:04) Live test 1: codebase exploration and architecture audit on ChatPRD(12:43) Live test 2: generating an HTML architecture and roadmap page(16:37) Live test 3: redesigning the How I AI landing page in Cursor(20:57) Live test 4: 45-minute autonomous task, pulling Sentry errors and Vercel logs(22:35) Where it struggled(23:49) My verdict on the output(25:23) Cost breakdown—Tools referenced:z.ai: https://z.aiGLM 5.2: https://z.ai/blog/glm-5.2OpenRouter: https://openrouter.aiCursor: https://cursor.comClaude Code: https://docs.anthropic.com/en/docs/claude-codeSentry: https://sentry.ioVercel: https://vercel.com—Other references:SWE-Bench Pro leaderboard (coding benchmark scores referenced in episode): https://www.swebench.comFrontier Suite and Post-Train Bench (additional benchmarks cited): https://scale.com/leaderboardUse Claude Code with OpenRouter: https://openrouter.ai/docs/cookbook/coding-agents/claude-code-integration—Where to find Claire Vo:ChatPRD: https://www.chatprd.ai/Website: https://clairevo.com/LinkedIn: https://www.linkedin.com/in/clairevo/X: https://x.com/clairevo—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].
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GLM 5.2: why I’m replacing Opus in Claude Code with this new model
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