GLM-5.2 from Z.ai: Is this Chinese model truly a "Claude killer"? Expert analysis
A sensation is brewing in the world of artificial intelligence. The new open-source model GLM-5.2 from the company Z.ai, according to many enthusiasts, poses a serious challenge to Anthropic's flagship products—the Claude family of models. Some have already rushed to call it the "Chinese killer" of Claude, and there are good reasons for this.
Let's figure out what GLM-5.2 actually is and how justified such bold claims are. This is not just another update. The main innovation is an expanded context window of 1 million tokens, which is five times larger than its predecessor GLM-5.1. This allows the model to keep entire codebases in view and conduct long, complex sessions without losing quality. Additionally, the model offers two "reasoning enhancement" modes: High for balancing performance and token consumption, and Max for maximum accuracy, but with increased resource usage.
The key advantage is the open-source MIT license, which removes regional restrictions and allows running the model on your own hardware (self-hosting). This makes GLM-5.2 incredibly attractive for developers and companies concerned about data privacy.
Benchmarks: Numbers Don't Lie, But There Are Nuances
According to Z.ai's internal tests, GLM-5.2 indeed shows impressive results, especially in programming tasks. On the Terminal-Bench 2.1 test, it scored 81.0 points, coming very close to Claude Opus 4.8's score of 85.0 and significantly surpassing Gemini 3.1 Pro's 74.0. On SWE-bench Pro, the result was 62.1 compared to 58.4 for GLM-5.1, although it still lags far behind Opus 4.8's 69.2.
However, looking at other benchmarks, the picture becomes more complex. On NL2Repo, which evaluates generating an entire project from a text description, GLM-5.2 (48.9) significantly trails Opus 4.8 (69.7). On DeepSWE, the gap is even larger: 46.2 versus 58.0. That is, in a number of complex, comprehensive scenarios, the Chinese model still falls short of the leader.
Nevertheless, on long-horizon tasks such as FrontierSWE, where the model must manage a project for dozens of hours, GLM-5.2 lags behind Opus 4.8 by only 1%, while outperforming GPT-5.5 and the previous version Opus 4.7. This suggests that the newcomer excels at maintaining context and consistency in long sessions.
Price and Real User Experience
The subscription cost for the GLM Coding Plan starts at $12.6 per month for the Lite tier (with annual payment), which is indeed several times cheaper than subscriptions to Claude or GPT. The Max tier will cost $112 per month. However, as users note, "the devil is in the details." The Max mode, in which the model reveals its potential, consumes significantly more tokens, which can quickly eat up the limit with active use.
User reviews are divided. On one hand, they praise the basic logic, which has become noticeably better, and the ability to autonomously solve complex problems by offering fixes. On the other hand, they criticize the unstable cloud infrastructure, the high cost of the Max mode, and the model's tendency to get stuck in endless reasoning loops, ignoring user commands. Many note that GLM-5.2 is "tuned" for benchmarks, but in real code work, it behaves like a "budget-tier" model.
My verdict: It is still premature to call GLM-5.2 a "Claude killer." It is undoubtedly the strongest open-source model available today, narrowing the gap with market leaders and offering unique advantages in the form of an open license and a massive context window. For developers who value privacy and are willing to tolerate some "teething problems" with the infrastructure, this is an excellent and cost-effective tool. However, for uncompromising quality and stability, Anthropic's and OpenAI's flagships remain unmatched. The AI market is becoming increasingly competitive, and this is certainly beneficial for all of us.