📄 中文摘要
在构建生产环境中的AI代理系统时，选择合适的LLM API至关重要。Anthropic、OpenAI和Google AI在API设计上存在显著差异，这些差异在代理需要处理速率限制、工具使用错误或在没有人工帮助的情况下进行身份验证时尤为明显。Rhumb对LLM API的评分与支付API相似，采用20个维度进行加权评估，以适应代理执行的需求。数据结果显示了各API在不同场景下的表现。
AI代理的LLM API：Anthropic、OpenAI与Google AI（AN评分数据）
出处: LLM APIs for AI Agents: Anthropic vs OpenAI vs Google AI (AN Score Data)
发布: 2026年3月29日
📄 English Summary
LLM APIs for AI Agents: Anthropic vs OpenAI vs Google AI (AN Score Data)
Choosing the right LLM API is crucial when building AI agent systems for production environments. Anthropic, OpenAI, and Google AI exhibit significant differences in their API designs, which become apparent when agents need to recover from rate limits, handle tool-use errors, or navigate authentication complexities without human assistance. Rhumb scores LLM APIs similarly to payment APIs, using 20 dimensions weighted for agent execution. The data reveals the performance of each API in various scenarios.