GLM-5
Overview
GLM-5 is Zhipu AI's new-generation flagship foundation model, specifically designed for Coding and Agent scenarios. It achieves State-Of-The-Art (SOTA) performance in open-source complex system engineering and long-horizon tasks, with a real-world coding experience approaching Claude Opus level.
Based on a 744B scale foundation model, combined with asynchronous reinforcement learning and sparse attention mechanisms, GLM-5 marks a paradigm shift from "writing code" to "building systems".
Key Features
- Parameter Scale and Data Volume: The base model's parameter scale has expanded to 744B (with 40B activated parameters), and pre-training data has increased to 28.5T, significantly enhancing the model's breadth and depth of knowledge.
- Ultra-Long Context and Output: Supports a context window of up to 200K tokens and a maximum output length of 128K tokens, enabling excellent performance in handling complex code repositories and multi-step tasks.
- Exceptional Coding & Agent Capabilities: Systematically strengthened programming capabilities, excelling in code generation with low hallucination rates and efficient token utilization.
- Multiple Thinking Modes: Offers various thinking modes to support more flexible and in-depth problem-solving.
Best Use Cases
- Complex System Engineering: Construction and management of complex software systems, assisting in system design and optimization.
- Long-Horizon Agent Tasks: Agent tasks requiring multi-step planning, execution, and feedback (e.g., automated workflows).
- High-Precision Code Debugging: Provides human-level coding assistance to improve development efficiency.
- Large-Scale Document Analysis: Deep information extraction and summarization for massive document sets.
Capabilities and Limitations
| Capability | Detailed Description |
|---|---|
| Reasoning Ability | Extremely Strong. Excels in complex logical reasoning and multi-step planning. |
| Creative Ability | Extremely Strong. Particularly adept at code generation and system design. |
| Multimodal Ability | Primarily focuses on text/code; can be integrated with visual tools on Zhipu platform. |
| Response Speed | 30-50 tokens/s. Balances high-quality output with efficient speed. |
| Context Window | 200K Tokens |
| Max Output | 128K Tokens |
Credits and Pricing
| Model | Input (Credits/Token) | Output (Credits/Token) |
|---|---|---|
| GLM-5 | 0.30 | 2.55 |
Note: For optimal performance in coding tasks, it is recommended to provide clear system prompts and utilize the 128K output capacity for building complete modules.