glm-4-air-250414

GLM-4-Air-250414 is a high-performance language model launched by Zhipu AI, primarily positioned as an intelligent agent task execution and complex logic processing engine. It excels in atomic capabilities such as tool calling, code generation, and instruction following.

• Performance rivals top international models: In benchmarks like BFCL-v3 (comprehensive tool calling) and TAU-Bench (intelligent agent tasks), some metrics are on par with or even surpass those of larger models such as GPT-4o and DeepSeek-V3.
• Atom-level capabilities optimized through reinforcement learning: By leveraging rejection sampling and reinforcement learning techniques, it significantly enhances performance in core intelligent agent tasks including instruction following, code generation, and function calling.
• Deeply tailored for enterprise-level scenarios: Particularly strengthened in engineering code generation and function-call capabilities, making it an ideal foundation for building intelligent agent applications.
• High cost-effectiveness: As a high-performance option within the GLM-4 series, it offers superior value for money compared to similar models, reducing the cost of intelligent agent development.
• Efficient and convenient development integration: Supports tool-calling capabilities such as Function Call, facilitating seamless integration with external systems (e.g., search engines, databases) and expanding application scenarios.

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Core Capabilities

🤖 Intelligent Agent Task Optimization:

Specifically enhances instruction-following and code-generation capabilities, perfectly suited for the atomic task execution scenarios required by intelligent agents.

🔧 Powerful Tool Calling:

Strengthens function-call capabilities, enabling seamless integration with external systems such as search engines and databases.

⚡ High-Performance Inference:

Pre-trained on 15T high-quality data and incorporating extensive synthetic inference data, laying a robust foundation for superior performance.

🌐 Deep Adaptation Across Multiple Scenarios:

Meets diverse needs including code generation, tool integration, and complex logic processing, making it the core engine for enterprise-level intelligent agents.