GLM-5.2 from Z.ai: Does the new Chinese model really "kill" Claude? Analyst's breakdown
In the crypto and tech communities, discussions are heating up around the new neural network GLM-5.2 from Z.ai. Enthusiasts have already dubbed it the "Chinese killer" of Anthropic's Claude, and some bloggers claim that at a price ten times lower, it outperforms its competitor in several scenarios. Let's figure out how true these claims are.
What is GLM-5.2 and what makes it powerful?
GLM-5.2 is a flagship model designed for long and complex work sessions. Its main advantage over its predecessor GLM-5.1 is a stable context window of 1 million tokens (compared to 200 thousand previously). This allows the model to keep entire codebases in focus without losing quality over ultra-long distances.
Key features of the model include two levels of reasoning enhancement: High for balancing performance and token consumption, and Max for maximum analysis depth. The model is distributed under the open MIT license, allowing it to be run on your own hardware (self-hosting). The API price remains at the level of the previous version.
Benchmarks: numbers don't lie
According to Z.ai's own tests, GLM-5.2 is recognized as the strongest open model on the market. However, it generally falls short of the flagship Claude Opus 4.8 in most cases. The gap with GLM-5.1 is noticeable: 81.0 vs. 63.5 on Terminal-Bench 2.1 and 62.1 vs. 58.4 on SWE-bench Pro. Meanwhile, on Terminal-Bench 2.1, the score of 81.0 closely approaches Opus 4.8 (85.0) and surpasses Gemini 3.1 Pro (74.0).
Comparison with competitors in maximum reasoning mode (Max) shows that GLM-5.2 confidently outperforms GPT-5.5 and Gemini 3.1 Pro on most tests but consistently lags behind Opus 4.8. For example, on SWE-bench Pro: 62.1 vs. 69.2 for Opus; on NL2Repo: 48.9 vs. 69.7. The exception is the Terminal-Bench 2.1 test, where the gap is minimal (81.0 vs. 85.0).
On ultra-long tasks (long-horizon), such as FrontierSWE, where the model works for tens of hours, GLM-5.2 lags behind Opus 4.8 by only 1%, surpassing GPT-5.5 and the previous version Opus 4.7. However, on SWE-Marathon with tasks at the level of compiler creation, the gap reaches 13%. Nevertheless, on all three tests, GLM-5.2 shows the best result among open models.
Price and pitfalls: cheap, but not for everyone
The GLM Coding Plan subscription is divided into three tiers: Lite ($12.6/month), Pro ($50.4/month), and Max ($112/month) with an annual payment discount of 30%. Quota consumption depends on load: a 3x multiplier during peak hours (14:00-18:00 Beijing time) and 2x off-peak. Until the end of September, a promotion is active where off-peak usage is billed at 1x.
However, users note that the model fully reveals itself only in Max mode, which consumes significantly more tokens. The cloud infrastructure, despite a good mathematical model, is described as extremely weak, and support as insufficient. Many developers complain that it's easier to pay for Claude or GPT than to deal with Z.ai's pricing.
Community opinion: enthusiasm and criticism
Strengths based on reviews: the model is called the strongest open neural network at the moment. Basic logic is noticeably better than version 5.1, and in programming, the model is comparable to GPT-5.5 at a high reasoning level. The AI autonomously performs complex tasks through auxiliary agents and itself suggests fixing noticed flaws.
Criticism primarily concerns service and stability: the cloud infrastructure is weak, pricing is expensive, and support leaves much to be desired. The neural network is criticized for a tendency to get stuck in infinite loops and ignore commands. According to users, the model is tailored exclusively for benchmarks, not for real production.
My conclusion: GLM-5.2 is undoubtedly a breakthrough among open models. It narrows the gap with leaders, especially in long-term scenarios, and offers an excellent price-to-performance ratio for self-hosting. But calling it a "killer" of Claude is premature. On most tests, Opus 4.8 remains ahead, and the user experience with Z.ai's cloud infrastructure is far from ideal. It is a strong competitor that will push the market to move faster, but not a "killer."