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Guide for using Google Gemini model API
Dealing with long response times when calling the Gemini 3 Flash Preview model is a common challenge for developers. In this post, we'll dive into configuration tips for key parameters like timeout, max_tokens, and thinking_level to help you master response time optimization for Gemini 3 Flash Preview. Core Value: By the end of this guide, … Read more
Handling AI understanding for huge video files has always been a pain point for developers—uploads timeout, base64 encoding causes memory overflows, and APIs return 413 errors. The good news is that in January 2026, Google significantly boosted Gemini API's file handling capabilities: inline upload limits increased from 20MB to 100MB, Files API now supports up … Read more
When working with the Google Gemini API, migrating from AI Studio to Vertex AI is a transition most developers eventually make. However, a seemingly minor difference in the role parameter has tripped up plenty of developers: [&{Please use a valid role: user, model. (request id: xxx) 400 }] The root cause of this 400 error … Read more
Want your AI to "think before it speaks" just like a human? Gemini Thinking mode is Google's latest deep reasoning feature, allowing models to showcase their complete thought process before delivering an answer. In this post, we'll dive into how to correctly configure Gemini Thinking mode in two popular AI clients: Cherry Studio and Chatbox. … Read more
Author's Note: A deep dive into the core differences between Google AI Studio and Gemini, analyzing their functional positioning and Nano Banana Pro usage limits, while providing alternatives for API calls and subscriptions. Many people struggle to tell the difference between Google AI Studio and Gemini: both can handle conversations, both are Google products, yet … Read more
