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Gemini 3.5 Flash Developer Guide

Gemini 3.5 Flash Developer Guide

Tech Google AI Studio (via X)
Google's Gemini 3.5 Flash model is now generally available, introducing features like "Thinking," multimodal function responses, and robust agentic execution for coding and long-horizon tasks.
What: Google has made its Gemini 3.5 Flash model generally available, featuring improvements such as a "Thinking" capability for agents, structured outputs with tools, multimodal function responses, code execution with images, and combined tool use, designed for sustained frontier performance in agentic execution and long-horizon tasks.
Why it matters: The focus on "Thinking" and enhanced tool use in Gemini 3.5 Flash reflects a clear industry direction towards more autonomous and capable AI agents that can tackle complex, multi-step tasks across different modalities, signaling Google's continued push in the highly competitive LLM space.
Takeaway: Developers can now explore the Gemini 3.5 Flash API and migration guidance to integrate its new features, especially for agentic workflows or tasks requiring multimodal understanding and structured outputs.
Decoder
  • Agentic execution: The ability of an AI model to autonomously plan, execute, and iterate on complex tasks, often by breaking them down into sub-tasks and using external tools.
  • Multimodal function responses: The capability of an AI model to use information from multiple modalities (e.g., text, images) when calling external functions or responding to prompts.
  • Long-horizon tasks: Complex tasks that require multiple steps, sustained reasoning, and often involve memory or planning over extended interactions.
Original article

Gemini 3.5 Flash is now generally available. This guide contains an overview of improvements, API changes, and migration guidance for the model. Gemini 3.5 Flash features Thinking, structured outputs with tools, multimodal function responses, code execution with images, and combined tool use, but not Computer Use. It delivers sustained frontier performance in agentic execution, coding, and long-horizon tasks at scale.

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