← GLM 5.2
Matt Wolfe
GLM-5.2 - The Open Model That's As Good As Opus!
⏱ 29 min video · 3 min read1 Jul 2026Worth watching
TL;DR
Matt Wolfe tests GLM 5.2, a 753-billion-parameter open-weight model from Chinese lab ZhipuAI, putting it through coding, document analysis, Chrome extension building, game cloning, and agentic workflows. The key finding: it delivers near-frontier performance at a fraction of the cost, making it a serious option for token-heavy and code-heavy tasks.
Key points
1
GLM 5.2 has a 1 million token context window, 128K max output, MIT open-source license, and costs dramatically less than frontier models like Claude Opus 4 or GPT 5 — yet performs comparably on coding and agentic tasks.
2
Despite being open-weight, it is NOT practically runnable on consumer hardware — the model is 753B parameters, weights exceed 1.5TB, and even a 1-bit quantized version needs ~200GB of memory.
3
Used inside Cursor as an agent harness, GLM 5.2 built a functional Mega Bonk 3D game clone in 6 prompts, a working Chrome extension (Page Brief) in 2 prompts, and organized a downloads folder autonomously.
4
Major companies are already switching to Chinese open-weight models: Lindy uses DeepSeek V4, Cursor uses Kimi 2.5, and Coinbase uses GLM 5.2 — largely because they are cheaper, more controllable, and not subject to US government bans.
5
Sam Hogan's inference.net gateway allows production teams to safely shadow-test GLM 5.2 alongside their existing model (e.g. Claude Opus) using mirrored live traffic before committing to a switch.
Actionable insights
→
Start with the ZhipuAI website for free, no-API testing of GLM 5.2 — the free tier appears generous with no obvious usage cap discovered during testing.
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For serious coding or agentic tasks, plug GLM 5.2 into Cursor (it is listed natively as a selectable model) or tools like Open Code — this gives it file access, terminal control, and multi-step task execution.
→
Use inference.net to shadow-test GLM 5.2 in production: it mirrors live traffic to GLM alongside your current model, runs automated evals, and sends a Slack alert when it is safe to switch — zero production risk.
Notable quotes
“Cheap capable models are going to change how you actually use AI. If a task is expensive, you're going to hesitate. If it's cheap, you're going to experiment.”
“The open weight part is important and it's very cool. But it's not because this is a model that you can just run locally on your own computer now because most people won't and most people can't. It mostly matters because it creates good competition.”
“Once they're out there and available, well, they really can't be taken away from us.”
Worth watching?
✅
Worth watching the full video?
Watch if you want to see live demos of GLM 5.2 building real apps inside Cursor — the key specs, use cases, and cost arguments are all captured here, so skip the video unless you want to see the actual output quality firsthand.
Saved you some time? The creator still deserves a like.
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