One of the main reasons I see why it took 19 seconds to run in Node.js is because the Vertex AI SDK for Node.js lets you use the Vertex AI Gemini API to build AI-powered features and applications. Both TypeScript and JavaScript are supported. The sample code in this document is written in JavaScript. There are additional installations that might take some time before it fully executes the code.

Key Factors Contributing to Latency Differences:

• Network Latency: Direct communication within the Vertex AI platform in Studio often results in lower latency compared to network requests in Node.js applications.

• Model Loading Time: Models might be pre-loaded or cached in Studio, reducing initial load times. In Node.js, models need to be loaded for each request.

• Prediction Request Processing: Studio might have optimized request handling, while Node.js applications may have additional overhead for data serialization, deserialization, and error handling.

Tips for Optimizing Node.js Performance:

• Minimize Network Latency: Choose a Vertex AI region closer to your Node.js application.

• Optimize Model Loading: Implement caching or batching techniques.

• Efficient Request Handling: Use asynchronous operations and minimize data transfer.

• Profiling and Optimization: Use profiling tools to identify bottlenecks and optimize your code.