GLM-4.5: The Chinese Open Model Outperforming Global Giants

Imagine an artificial intelligence that not only reasons like a human but can also independently code, browse the web, and create entire PowerPoint presentations based on a simple description—even in Czech. This is the reality of the new GLM-4.5 model from the Chinese company Zhipu AI, also known as Z.ai. Released in late July 2025, this open model delivers revolutionary advances in agentic capabilities, reasoning, and programming. According to the official Z.ai blog and an analysis by VentureBeat, GLM-4.5 ranks third among global models across 12 key benchmarks, outperforming models such as Claude 3.5 Sonnet and Gemini 1.5 Pro in some tests. And the best part? It is available for free under the Apache 2.0 license, allowing developers to freely use, modify, and deploy it.

GLM-4.5 is not just another large language model (LLM). It is designed specifically for complex tasks that combine reasoning, coding, and interaction with tools. Zhipu AI, founded in 2019, has raised more than $1.5 billion in investments from giants such as Alibaba and Tencent. According to CNBC, this made it possible to create a model that runs on just eight Nvidia H20 graphics cards, half as many as similar models from DeepSeek require. This makes GLM-4.5 not only powerful but also economically accessible for widespread use.

The Architecture and Training That Make GLM-4.5 So Exceptional

GLM-4.5 is based on a Mixture-of-Experts (MoE) architecture that combines 355 billion total parameters with 32 billion active parameters. The lighter GLM-4.5-Air version has 106 billion total and 12 billion active parameters, making it ideal for less demanding applications. According to the Z.ai blog, this structure increases the model's depth (more layers), improving reasoning, while reducing its width for greater efficiency. The model uses Grouped-Query Attention with 96 heads for better processing of contexts of up to 128,000 tokens, as well as Multi-Token Prediction for faster inference.

Training took place in several stages: First on 15 trillion tokens from a general corpus, then on 7 trillion tokens of specialized coding and reasoning data. The next stage added 1.1 trillion tokens from repository-level code, synthetic reasoning inputs, and long contexts. Zhipu AI used its own RL infrastructure called slime, which separates data generation from training to improve efficiency. Techniques such as mixed-precision rollouts and adaptive curriculum learning enabled the model to gradually master increasingly complex tasks, from simple ones to agentic tasks.

The result is a model that supports two modes: "thinking" for complex reasoning and tool use, and "non-thinking" for quick responses. According to VentureBeat, this enables entire PowerPoint presentations to be created automatically from just a title or prompt, which is useful for meetings, education, or reports.

Benchmark Performance: Outperforming the Competition

GLM-4.5 excels in tests of agentic tasks, reasoning, and coding. In the BrowseComp benchmark, it achieves 26.4% accuracy, outperforming Claude 3 Opus (18.8%) and approaching o1-mini-high (28.3%). It scores 79.7 in TAU-bench-Retail, 60.4 in TAU-bench-Airline, and 77.8 in BFCL v3. This puts it on par with Claude 3.5 Sonnet.

It also scores highly in reasoning: 98.2% in MATH 500, 91.0% in AIME24, and 79.1% in GPQA. In coding, it achieves 64.2% in SWE-bench Verified and 37.5% in Terminal-Bench, outperforming GPT-4o (48.6% in SWE-bench) and Qwen2-Coder (an 80.8% win rate in pairwise comparisons). GLM-4.5-Air, the lighter variant, ranks sixth overall, with similar results but lower hardware requirements.

According to additional information from sources such as MarkTechPost and Pandaily, GLM-4.5 is the first open model to natively integrate reasoning, coding, and agentic capabilities. It is licensed under MIT and available on Hugging Face, making it ideal for integration into platforms such as Aurora Mobile's GPTBots.ai.

Practical Examples and Applications: From Games to Presentations

Zhipu AI has presented several demos showcasing the model's power. For example, GLM-4.5 can create a clone of the game Flappy Bird, a 3D maze, or a TODO list with drag-and-drop functionality—all in HTML, SVG, or Python. When creating presentations, the agent autonomously searches for information on the web and generates slides, such as presentations about cyclist Tadej Pogačar's achievements or the Big Bang theory.

Other examples include full-featured web applications: a Pokémon Pokédex with type filtering, a medieval poem generator, or cyberpunk cards. These features are available directly on the Z.ai platform or through an API compatible with OpenAI standards. API prices are low: $0.60 per million input tokens for GLM-4.5 and $0.20 for Air, with output priced at $2.20 and $1.10.

The model supports creative writing, emotive copywriting, and dialogue systems for customer support or role-playing. Integration with tools such as CodeGeex or Roo Code enhances its agentic coding capabilities, where it achieves a 90.6% success rate in tool-calling, outperforming Claude 3.5 Sonnet (89.5%).

Availability and Market Impact

GLM-4.5 is available on Z.ai, through its API, Hugging Face, and ModelScope. It supports inference via vLLM and SGLang for local deployment. According to VentureBeat, it is part of a wave of open Chinese models, such as Alibaba's Qwen and Moonshot's Kimi K2, that are putting pressure on American giants such as Meta and OpenAI.

For businesses, GLM-4.5 reduces dependence on proprietary models thanks to streaming, context caching, and structured JSON responses. It is ideal for teams with limited budgets, reducing costs by up to 90% compared with Claude. However, as a Chinese model, it may be subject to local regulations, which is important in terms of data control.

At a time when AI is becoming an everyday part of life, Zhipu AI's GLM-4.5 delivers accessible power that could change how we work with technology. If you are looking for a model that is fast, smart, and open, this is the one.