GLM-4.5-Air

System Requirements

VRAM requirements for different quantization methods and context sizes

About GLM-4.5-Air

GLM-4.5-Air is a high-efficiency large language model developed by Z.ai as part of the GLM-4.5 series. It is designed to bridge the gap between massive-scale foundation models and the practical constraints of on-device or mid-range cloud deployments. Optimized primarily for agent-oriented workflows, the model prioritizes reasoning, complex instruction following, and code generation. It functions as a versatile engine for autonomous agents capable of multi-step planning and tool invocation, making it a viable selection for developers building sophisticated digital assistants and automated software engineering pipelines.

Architecturally, the model utilizes a sparse Mixture-of-Experts (MoE) framework, featuring 106 billion total parameters with only 12 billion active per forward pass. This design incorporates 128 routed experts and a specialized shared expert layer, activating 9 experts per token to maintain representational capacity while significantly reducing computational overhead. The transformer block is further enhanced by a Multi-Token Prediction (MTP) layer, which allows the model to predict several future tokens simultaneously. This implementation facilitates speculative decoding, which increases inference throughput and provides a responsive experience for real-time interactive applications.

Technical innovations in GLM-4.5-Air include the adoption of Grouped-Query Attention (GQA) with 96 attention heads and 8 key-value groups, reducing memory bandwidth requirements during long-context processing. The model supports a 128,000-token context window using Rotary Positional Embeddings (RoPE) and features a hybrid reasoning system. This system allows for a deliberate thinking mode, which executes a latent chain-of-thought process for analytical problem-solving, and a standard mode for immediate output. Native integration for function calling, web browsing, and code execution ensures the model can interact with external environments with high reliability.

Technical Specifications

Resources

About GLM Family

General Language Models from Z.ai

Other GLM Family Models

• GLM-4-9B-Chat
• GLM-4V
• GLM-4-9B
• GLM-4-9B-Chat-1M
• GLM-4
• GLM-130B
• GLM-4.5