◉GEMINI LABJP
●ROBOTICS — The ER 1.6 preview that shut down on August 31 does have a successor. Gemini Robotics ER 2 is in public preview, in both standard and streaming variants●VIDEO — ER 2 judges success and failure from live video rather than still snapshots, which is what lets it catch spills, slips, and misalignments while a task is still running●DEADLINE — Next up is September 30, when gemini-omni-flash-preview is retired. The target is gemini-omni-1.1-flash, GA since August 27, and there are now under four weeks left●APIKEY — Every remaining standard API key, restricted ones included, stops working during September. The replacement is an auth key bound to a Google Cloud service account●PRICE — Gemini 3.7 Flash keeps its introductory $0.75/$3.75 per 1M through December 31, then moves to $1.50/$7.50 on January 1, 2027. Any estimate crossing the year needs both figures●AUDIO — Gemini 3.5 Transcribe handles language detection across 85+ languages, speaker diarization, word-level timestamps, and custom vocabulary biasing of up to 1,000 terms●ROBOTICS — The ER 1.6 preview that shut down on August 31 does have a successor. Gemini Robotics ER 2 is in public preview, in both standard and streaming variants●VIDEO — ER 2 judges success and failure from live video rather than still snapshots, which is what lets it catch spills, slips, and misalignments while a task is still running●DEADLINE — Next up is September 30, when gemini-omni-flash-preview is retired. The target is gemini-omni-1.1-flash, GA since August 27, and there are now under four weeks left●APIKEY — Every remaining standard API key, restricted ones included, stops working during September. The replacement is an auth key bound to a Google Cloud service account●PRICE — Gemini 3.7 Flash keeps its introductory $0.75/$3.75 per 1M through December 31, then moves to $1.50/$7.50 on January 1, 2027. Any estimate crossing the year needs both figures●AUDIO — Gemini 3.5 Transcribe handles language detection across 85+ languages, speaker diarization, word-level timestamps, and custom vocabulary biasing of up to 1,000 terms
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Introducing Gemini Lab

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What is Gemini Lab?

Gemini Lab is a bilingual knowledge base dedicated to Google's Gemini family of large language models. We cover everything from basic usage guides to advanced API development and prompt engineering techniques, all available in both Japanese and English.

Gemini Lab is part of a family of sister sites built on a shared technology stack. Alongside Claude Lab for Claude AI, Antigravity Lab for Google's experimental coding tools, and Rork Lab for mobile app development, our mission is to provide well-organized, practical knowledge about modern AI and development tools.

Why a Dedicated Gemini Knowledge Base?

Since the release of Gemini 2.0 in late 2024, Google's AI platform has evolved at a remarkable pace. Gemini 2.5 Pro and Flash introduced thinking models and enhanced multimodal processing in 2025. Now in 2026, the Gemini 3 series and the latest 3.1 Pro and Flash-Lite models have significantly expanded the lineup.

Keeping up with this rapid evolution requires systematic information organization. While official documentation is comprehensive, practical guides with real-world examples remain scarce. Gemini Lab was created to fill this gap with hands-on tutorials and in-depth technical content.

Content Categories

We currently publish articles across four main categories.

Gemini Basics — Introductory content for those getting started with Gemini, including overviews of what Gemini is, how to choose between Pro and Flash, and business use cases.

Developer Tools — Guides for developer-facing tools such as Gemini CLI, Google AI Studio, and Gemini Extensions, covering setup, workflows, and best practices.

API / SDK — Implementation-focused articles on the Gemini API, including quickstart guides, streaming, multimodal input, and logging and dataset management.

Advanced Usage — Deep dives into Gemini's cutting-edge features like Function Calling, Grounding with Google Search, and text-to-speech synthesis.

Technical Highlights

Gemini Lab is built with Next.js 16 and TypeScript, hosted on Cloudflare Workers. Articles are managed in MDX format with full bilingual support. Code blocks feature syntax highlighting powered by rehype-pretty-code and shiki, optimized for both dark and light themes.

We've also implemented llms.txt for AI search engine compatibility and comprehensive JSON-LD structured data for enhanced SEO.

What's Next

The Gemini ecosystem continues to expand rapidly. We plan to cover topics including detailed Gemini 3.1 Pro and Flash-Lite benchmarks, practical Gemini CLI workflows, integration patterns with Firebase and BigQuery, agent-building tutorials, and comparisons with other leading LLMs.

This blog will also serve as a hub for site updates and the latest Gemini news. Stay tuned, and thank you for visiting Gemini Lab!