GLM-4.6

Z.AI's Mixture-of-Experts model for Agentic, Reasoning & Coding applications

Focus on agentic intelligence, reasoning and coding

The GLM-4.6 model at a glance

GLM-4.6 from Z.AI is a state-of-the-art language model that has been specially developed for demanding application areas such as agentic systems, precise reasoning and complex code generation. Through a combination of efficient mixture-of-experts architecture, deep neural structures and a reinforcement-optimized training process, GLM-4.6 offers outstanding performance in benchmarks – and highest reliability in real-world applications. Ideal for anyone who needs scalable AI solutions with tool integration and thinking mode.

Name:

GLM-4.6

Developer:

Z.AI (Zhipu AI Inc.)

Publication:

September 2025

License:

Apache 2.0 (open source, commercially usable)

Model type:

Mixture-of-Experts (MoE) language model

Parameters:

355 billion (of which 32B active per token)

Architecture:

MoE, 200k context, grouped query attention, 96 attention heads, deep architecture, QK standard, multi-token prediction (MTP) layer

Tokenizer:

Unigram, 160k vocabulary

Context length:

128,000 tokens

Specialties of GLM-4.6

Hybrid Reasoning & Thinking Mode

GLM-4.6 offers a “thinking mode” for complex reasoning and tool use as well as a fast mode for simple tasks. Switching is done via the thinking.type parameter.

Agentic Intelligence & Tool Usage

Optimized for agents, coding agents, tool use and web browsing. Native function calling and high success rate for tool integration.

Deep architecture & MoE efficiency

GLM-4.6 relies on many layers and a high attention head count for better reasoning capabilities with high efficiency through MoE.

Reinforcement Learning & Curriculum

Multi-level RL training with specialized curricula for reasoning, coding and agentic tasks.
Individual AI consulting

Is the GLM-4.6 the right model for you?

We would be happy to advise you individually on which AI model suits your requirements. Arrange a no-obligation initial consultation with our AI experts and exploit the full potential of AI for your project!

The post-training pipeline for GLM-4.6

Training data & training process

GLM-4.6 was trained in a multi-stage training process on 15 trillion tokens of general data and an additional 7 trillion tokens of specialized data for reasoning, code and agentic tasks. The curriculum was specifically tailored to real-world requirements through reinforcement learning – including function calling, web browsing and tool usage.

The use of Expert Distillation and structured multi-stage training ensures that GLM-4.6 is not only convincing in benchmarks, but also in practical use with high robustness and accuracy.

Hardware-Anforderungen (Inferenz)

  • Recommended inference engines: vLLM, SGLang, KTransformers
  • Checkpoints available in block-fp8 and other formats
  • Several high-end GPUs are recommended for real-time inference (e.g. 2-4x H200, RTX 6000 Pro Blackwell)
  • Quantized variants and adapters available
Fast & precise

Recommended use cases for GLM-4.6

Is GLM-4.6 the right AI model for your individual application? We will be happy to advise you comprehensively and personally.

AI assistants and chatbots with tool integration
Automated problem solving and decision support
Complex code generation and software development
Scientific research, mathematics, data analysis
Agentic workflows, web browsing, autonomous systems
GLM-4.6
GLM-4.6: Precise answers & reliable automation

Ready for hybrid reasoning and agentic workflows?

Whether you want to develop a functional AI agent with tool use or automate complex decision-making processes: GLM-4.6 provides the architecture, flexibility and scalability that modern AI applications need today. We advise you individually on integration, hosting and operation – on request with infrastructure from our German data center.