●NANOLITE — Nano Banana 2 Lite is here: Google's fastest and most cost-efficient Gemini Image model, made for running lightweight image generation cheaply●OMNIFLASH — Gemini Omni Flash is in public preview, a natively multimodal model that lets enterprises and developers build custom, dynamic video workflows●AGENTS — Managed Agents expand with background: true for async server-side runs and polling, remote MCP server integration, and refreshing credentials across interactions●MEMORY — The Memory Bank IngestEvents API is generally available, decoupling event ingestion from memory generation so you can stream content continuously●THROUGHPUT — Provisioned Throughput now lets you submit up to seven pending orders for the same model and region●DEPRECATE — Image generation models shut down on August 17, and the Grok 4.1 family on the Gemini Enterprise Agent Platform on August 20●NANOLITE — Nano Banana 2 Lite is here: Google's fastest and most cost-efficient Gemini Image model, made for running lightweight image generation cheaply●OMNIFLASH — Gemini Omni Flash is in public preview, a natively multimodal model that lets enterprises and developers build custom, dynamic video workflows●AGENTS — Managed Agents expand with background: true for async server-side runs and polling, remote MCP server integration, and refreshing credentials across interactions●MEMORY — The Memory Bank IngestEvents API is generally available, decoupling event ingestion from memory generation so you can stream content continuously●THROUGHPUT — Provisioned Throughput now lets you submit up to seven pending orders for the same model and region●DEPRECATE — Image generation models shut down on August 17, and the Grok 4.1 family on the Gemini Enterprise Agent Platform on August 20

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Android development

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Android Studio² Gemma 4² Ollama² local LLM² fine-tuning¹ CI/CD¹ offline AI¹ Gemini Code Assist¹

⬡ Gemini Advanced/2026-05-06Advanced

Production-Grade Gemma 4 + Ollama + Android Studio — Task Routing, Fine-Tuning, Team Deployment, and CI Integration

A deep-dive into running Gemma 4 locally for Android development at production scale. Covers model-routing proxies, LoRA fine-tuning for project-specific patterns, Docker Compose team setup, and GitHub Actions AI code review integration.

⟐ Gemini Dev/2026-05-06Intermediate

Running Gemma 4 Locally in Android Studio via Ollama — Setup, Performance, and Real-World Development Experience

A hands-on guide to connecting Android Studio's local LLM feature with Gemma 4 via Ollama. Covers MacOS setup, model selection, practical coding experience, and when local AI makes more sense than cloud APIs.