◉GEMINI LABJP
●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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⟐ Gemini Dev/2026-06-24Intermediate

Folding a Local Gemma 4 into Daily Work — Practical Notes on the Ollama API and Response Speed

Taking a local Gemma 4 you can now run interactively and folding it into real work: how to hit Ollama's local API from a script, tricks to improve perceived response speed, and a two-tier fallback that automatically routes to the cloud Gemini API — code included.

⟐ Gemini Dev/2026-06-24Beginner

Running Gemma 4 Locally on Windows — A Hands-On LLM in Two Commands with Ollama

How to run Google's lightweight open model Gemma 4 locally on a Windows laptop. With Ollama, you go from install to running in effectively two commands. Plus how to split work between the cloud Gemini API and a local Gemma.

⬡ Gemini Advanced/2026-04-09Advanced

Gemma 4: From Edge E2B to Cloud 31B—Choosing the Right Model and Implementation Patterns

Comprehensive exploration of Google DeepMind's Gemma 4 family (E2B/E4B/26B A4B/31B). Master MoE architecture, 256K context windows, native thinking mode, and multimodal capabilities. Learn edge deployment strategies, production implementations, and fine-tuning best practices.