GLM 5.2: why I’m replacing Opus in Claude Code with this new model

What if I told you you could get opus level reasoning at a fraction of the cost? That's what we're gonna see and test today when I take a look at GLM 5.2. This is our first of many reviews of OpenWay and open source models to see if we should all be paying the tax to Anthropic and OpenAI or if we can run these models locally and get the same results. Let's dive in. This episode is brought to you by Mercury, banking redesigned from the ground up now with Command, so you can just say what you need and the work gets done. I've always liked products that reduce the distance between knowing what you wanna do and actually doing it. That's one reason I've been a Mercury customer for years. Whether it's sending money, managing cards, or checking in on the business, Mercury has always felt fast, simple, and built for founders. What I love about Mercury Command is that it takes that idea even further. Instead of navigating menus or figuring out where a feature lives, you just say what you need. Ask a question about your finances, create an invoice, categorize transactions, or send a payment, all from a conversation. Because command is built directly into Mercury, every answer comes from your actual account data, and every action follows the permissions and controls you've already set up. It feels like where software is less navigating and more simply telling a product what you want to accomplish. Visit mercury.com to learn more and apply online in minutes. Mercury is a fintech company, not an FDIC insured bank, banking services provided through Choice Okay. Before I get GLM 5.2 running against some benchmarks on my own computer, my own projects, I wanna talk you through what exactly this model is. So GLM stands for general language model, and this is a model that's put out by the Beijing based startup, z dot a I. So, yes, this is a Chinese trained model. Now this model is open weight. You may have heard that term before, but not exactly known what it means. And all it means is that the trained model weights are publicly available for download, which allows you to run it on your own hardware. You can fine tune that model on your own data, and you can inspect how it works. Now the licenses for open weight models kind of depends, so it doesn't necessarily mean you can use it, quote, unquote, for free. But why this matters for GLM 5.2 is you can self host this. So let's say you have one of those chunky Mac studios at home where you wanna run some models locally. You could potentially run GLM 5.2 locally. You can fine tune it, which means you can adapt it to your purpose. And then the thing that people really love about these open weight models is they're cheap. You can run your own inference, and so it …