GLM-5.2 is the step change for open agents

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GLM-5.2 is the step change for open agents<br>A capability threshold I've been carefully monitoring.<br>Nathan Lambert<br>Jun 22, 2026

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Audio playback is not supported on your browser. Please upgrade.Housekeeping: Following my “State of the blog” post last week, noting a slight increase in paid features, it’s a good time to remind folks that I offer group subscriptions with larger discounts proportional to the number of seats.<br>I also released a new paper today on open RL recipes for terminal agents, read more here.<br>A bit over a week ago, when the AI world was still reeling from the shocking export restriction, and effective banning, of Claude Fable 5, Z.ai released their latest model, GLM-5.2. This model was rolled out unusually on a Saturday, June 13th, to GLM Coding Plan members. This is an unusual release practice, normally when an AI model is released on a weekend it’s for a weird reason (most famously, Llama 4).1 In this case, it seemed like Z.ai was excited to capitalize on the zeitgeist of “Anthropic being anti open-science” with their silent safeguards on AI researchers. For the past year or two, the Chinese open-weight labs have taken every opportunity they have for easy marketing wins like this.<br>Share<br>GLM-5.2, in a common naming convention across the industry, looked potentially like an incremental update following the popular GLM-5.1 model. At this point, Moonshot AI, makers of the Kimi models, and Z.ai, makers of the GLM models, have consolidated the top of the reputational market with the most beloved open-weight models among AI researchers. What unfolded is a common lesson in tracking AI models that often minor version numbers can have AI models crossing meaningful user experience thresholds. A small change in benchmarks and training can open a wide range of new use-cases.<br>What has followed is a slow, groundswell of hype for GLM-5.2. The official, MIT-licensed model weights and release blog dropped three days after the initial rollout, on June 16th. One could ramble many technical details, such as the strong benchmark scores, the very popular RL framework that Z.ai uses (SLIME), the recommendation of always using the model on Max thinking effort, and so on, but the initial release blogs usually aren’t the thing to focus on. You can wait and read the ecosystem reaction to know if it’s the real deal. Benchmarks are half dead these days, anyways.

What followed on the 16th was a slew of community benchmarks showing better-than-expected results for GLM-5.2. Arena’s agent leaderboard had it as the only open model mixing it up with OpenAI and Anthropic’s latest models (notably matching Opus 4.8’s no-thinking effort to GLM-5.2’s max mode). This is one of many evals GLM-5.2 is crushing Gemini on, but that’s a topic for another time. A benchmark that has mixed perception in the community (particularly among actual designers), Design Arena even had GLM-5.2 besting Claude Fable itself — the recently banned hype machine!<br>Pretty much everyone I respect among the AI commentariat and researcher class has praised the model after using it personally. Such a focal point of discussion among the community has only been so clear with an open model release once before — DeepSeek R1. This is not a comparison I make lightly, and when I compared Kimi K2’s release to a “DeepSeek Moment,” GLM-5.2 has well exceeded that. What made Kimi K2 impressive was that big steps in open model performance could seemingly come from anywhere in China. The step that GLM-5.2 has taken is more of a one way door for AI progress.<br>Anthropic’s record revenue growth rate on the back of Claude Code is heavily driven by being the best model, and the only model that can really do this. GLM-5.2 is the first of many (coming soon) open weight models to offer credible alternatives. The parallel is very clear, to when DeepSeek R1 showed that open-weight labs, with far fewer resources, could also replicate the chain-of-thought reasoning models that OpenAI championed with o1. As AI systems get more complex and far more expensive to build, with tools, integrated harnesses, and scaled model weights, it was not a given that this GLM-5.2 moment would happen at all.<br>The key point is that GLM-5.2 is the open weight model that feels right in coding harnesses as a general agent . It’s the first one. I was personally overdue in trying some of the recent peer models, such as Kimi K2.7 or GLM-5.1, but the hype was too much for me to ignore. I put it to work helping make content for my post-training course with Fireworks’ API in Claude Code (setting this up was very easy). There were some minor knife cuts, such as the Claude Code harness / my repo documentation trying to send images to the model, which would brick Fireworks API for the session — forcing a manual context clear. Overall, the model capabilities immediately felt right, and I still have some tinkering to do...