GLM-5.2: The Most Powerful Text AI Model

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Key Takeaways

1The GLM-5.2 model from Z.ai, launched in June, contains 753 billion parameters, surpassing its predecessors.

2GLM-5.2 dominates the Artificial Analysis Intelligence Index with a score of 51, outpacing its competitors.

3Despite its power, GLM-5.2 consumes more tokens per task than other open models, reaching 43,000 tokens.

💡Why it matters — GLM-5.2 could transform text-based AI, but its high token consumption presents efficiency challenges.

A Significant Launch for Z.ai with GLM-5.2

On June 13, the Chinese lab Z.ai unveiled its latest language model, GLM-5.2, to its coding plan subscribers. A few days later, on June 16, the model was made publicly available under an MIT license, allowing for broader use. This model stands out with its 753 billion parameters and a database of 1.51 terabytes, while incorporating 40 active parameters through the Mixture of Experts method. Unlike other models in the Z.ai family, GLM-5.2 is exclusively textual, while the GLM-5V-Turbo range focuses on vision but remains closed. One of the major advancements of GLM-5.2 is its ability to handle a context window of 1 million tokens, a significant improvement over the 200,000 tokens of its predecessor, GLM-5.1.

Rapid Recognition on Benchmarks

The arrival of GLM-5.2 has generated considerable interest, particularly from Artificial Analysis, an organization renowned for its independent benchmarks. GLM-5.2 quickly established itself as the benchmark model on the Artificial Analysis Intelligence Index. With an impressive score of 51, it surpasses competing models such as MiniMax-M3 and DeepSeek V4 Pro, which each scored 44, and Kimi K2.6 with 43.

Notable Token Consumption

Despite its performance, GLM-5.2 is distinguished by a higher token consumption than its competitors. During tests on the Intelligence Index, it was observed that GLM-5.2 uses an average of 43,000 output tokens per task. In comparison, GLM-5.1 uses 26,000, while MiniMax-M3, Kimi K2.6, and DeepSeek V4 Pro consume 24,000, 35,000, and 37,000 tokens, respectively.

Performance in Web Development

On the Code Arena WebDev leaderboard, GLM-5.2 managed to secure second place, just behind Claude Fable 5. This ranking evaluates the models' capabilities to handle front-end web development tasks, including agentic coding workflows. This performance is particularly remarkable given that GLM-5.2 does not process images, an element often deemed essential for front-end coding models.

User Experience and Cost

I had the opportunity to test GLM-5.2 via OpenRouter, which offers it through 9 different providers. The pricing is relatively competitive, with a cost of $1.40 per million tokens for input and $4.40 per million for output. In comparison, GPT-5.5 is offered at $5/$30 and Claude Opus 4.5-4.8 at $5/$25.

Varied Results in Graphic Generation

When using GLM-5.1, I was impressed by the quality of the generated SVGs, particularly a pelican and an opossum, where the model even added CSS animations in an HTML document. With GLM-5.2, I attempted to generate an SVG of a pelican on a bicycle. The result was a self-animated SVG, with no flaws in the animations, providing a high-quality vector illustration.

However, generating an SVG of an opossum on an e-scooter did not meet expectations. Unlike GLM-5.1, GLM-5.2 failed to animate the opossum, marking a notable regression in this specific case.