●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-api² production² embedding¹ semantic-cache¹ cost-optimization¹ cloudflare¹ rag¹ edge¹ workers¹

◈ Gemini API/2026-05-25Advanced

Designing a Semantic Cache for the Gemini API — Embedding-based Answer Caching That Actually Pays for Itself

A practical design for a semantic cache that sits in front of the Gemini API. Combines text-embedding-004, cosine similarity thresholds, versioned cache keys, and TTL design to balance hit rate and answer quality, with Python and Cloudflare Vectorize code that runs in production.

◈ Gemini API/2026-05-02Advanced

Building a Fully Edge RAG with Gemini API and Cloudflare Vectorize: A Production Guide for Low Latency, Low Cost, Global Delivery

Combine Gemini Embedding with Cloudflare Vectorize to ship a production RAG that runs entirely inside the Workers runtime — global latency, predictable cost, and a defensive layer covering subrequest limits, retries, and tenant isolation.