GLM-5.2 vs. Claude: Does the new Chinese model truly deserve the title of "killer"?
Chinese company Z.ai has released a new flagship neural network, GLM-5.2, and the developer community has already begun comparing it to Anthropic's products. Users claim that the model not only catches up to Claude in quality but also offers a significantly lower price. I analyzed the specifications, benchmarks, and reviews to understand whether such hype is justified.
What is GLM-5.2 and why is it interesting
GLM-5.2 is a model optimized for long working sessions. The main innovation is an expanded context window of up to 1 million tokens, which is five times larger than its predecessor GLM-5.1 (200 thousand). This allows the model to retain vast amounts of code or text in its field of view without losing quality.
Key features:
- Stable context window of 1 million tokens, which does not degrade during ultra-long sessions.
- Two levels of reasoning enhancement: High (balance of performance and token consumption) and Max (maximum capabilities, but with higher consumption).
- Open MIT license with no regional restrictions — can be run on your own hardware.
- API price remains at the level of version 5.1.
The model is already available on HuggingFace and ModelScope, and is also supported by popular frameworks: transformers, vLLM, SGLang, and others. The GLM Coding Plan subscription provides access to the ZCode desktop agent and integrations with Claude Code and OpenCode.
What the benchmarks show
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 Anthropic's flagship — Claude Opus 4.8 — in most cases.
On standard programming tests, the improvement compared to 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. On Terminal-Bench 2.1, the result 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:
| Benchmark | GLM-5.2 | GLM-5.1 | Opus 4.8 | GPT-5.5 | Gemini 3.1 Pro |
|---|---|---|---|---|---|
| SWE-bench Pro | 62.1 | 58.4 | 69.2 | 58.6 | 54.2 |
| Terminal-Bench 2.1 | 81.0 | 63.5 | 85.0 | 84.0 | 74.0 |
| NL2Repo | 48.9 | 42.7 | 69.7 | 50.7 | 33.4 |
| DeepSWE | 46.2 | 18.0 | 58.0 | 70.0 | 10.0 |
| ProgramBench | 63.7 | 50.9 | 71.9 | 70.8 | 39.5 |
| MCP-Atlas | 76.8 | 71.8 | 77.8 | 75.3 | 69.2 |
| Tool-Decathlon | 48.2 | 40.7 | 59.9 | 55.6 | 48.8 |
On long-horizon tasks, the picture is similar. On the FrontierSWE test, where the model manages open technical projects for tens of hours, GLM-5.2 lags behind Opus 4.8 by only 1%, but surpasses GPT-5.5 and the previous version Opus 4.7. On PostTrainBench, which evaluates the improvement of other models through fine-tuning, GLM-5.2 outperforms Opus 4.7 and GPT-5.5, yielding only to Opus 4.8.
On the ultra-long SWE-Marathon with tasks like creating compilers, the gap from Opus 4.8 is 13%. Nevertheless, on all three tests, GLM-5.2 shows the best result among open models.
How much does it cost and what's the catch
The GLM Coding Plan subscription is divided into three tiers (prices indicated with a 30% annual discount): Lite — $12.6/month, Pro — $50.4/month, Max — $112/month. The Pro plan provides five times the limit of Lite, and Max provides twenty times. Higher-tier plans receive priority access to flagship models, a set of additional tools, and dedicated resources during peak hours.
Within the subscription, quota consumption depends on load: a 3x coefficient during peak hours (from 14:00 to 18:00 Beijing time) and 2x off-peak. A promotion is active until the end of September, so off-peak usage is billed at 1x.
What users are saying
Opinions are divided. Strengths according to reviews:
- The model is called the strongest open neural network tried so far.
- Basic logic is noticeably better than version 5.1, and in programming, the model is comparable to GPT-5.5 at a high level of reasoning.
- The AI autonomously performs complex tasks through auxiliary agents and itself suggests fixing noticed flaws.
- Users describe it as slow and expensive, but extremely persistent in achieving its goal.
Criticism primarily concerns the service and stability:
- The cloud infrastructure, despite a good mathematical model, is called extremely weak.
- Developers complain about expensive pricing and poor support, noting that it's easier to pay for Claude or GPT.
- The neural network is criticized for its tendency to get stuck in infinite loops and ignore commands.
- According to users, the model is tailored exclusively for benchmarks.
Users also specifically note the operating modes. The model, they say, only reveals itself in Max mode, which consumes several times more tokens than High.
So, is it a "Claude killer" or not?
There is no clear answer to this question. GLM-5.2 is recognized as the best open model today for programming and autonomous tasks. In certain long scenarios, it comes very close to Anthropic's flagship. The open MIT license, the ability to run on your own hardware, and the low entry threshold make it a notable player.
At the same time, it is bloggers, not benchmarks, who call the new model a "Claude killer." On most tests, Z.ai itself places its model below Opus 4.8. Additionally, users complain about unstable cloud infrastructure, high token consumption in Max mode, and poor support. The new AI narrows the gap with the leaders but does not yet surpass them.
My analysis: GLM-5.2 is a step forward for open models, but calling it a "Claude killer" is premature. It is indeed competitive in price and performance on benchmarks, but in real-world scenarios, it falls short in stability and convenience. For enthusiasts and developers willing to tolerate its shortcomings for the sake of savings, it's an excellent option. For production — not yet.