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

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Gemini API16Indie Development5Context Caching4Python3Image Classification2gemini-embedding-22Batch Processing2operations2Gemini 3.5 Flash2Production2Indie Developer2production2
Gemini API/2026-05-24Advanced

Apple Vision Framework × Gemini API: Hybrid Image Recognition — Cutting Wallpaper App Cloud Inference Costs by 70%

How I built an on-device prefilter with Apple Vision Framework to cut Gemini Vision API calls by more than half in my iOS wallpaper app. Real cost, accuracy, and latency numbers, with the gotchas an indie developer hits along the way.

Gemini API/2026-05-06Intermediate

One Month with Gemini 2.5 Flash: An Indie Developer's Honest Cost and Performance Report

Real cost, speed, and quality data from running Gemini 2.5 Flash across three indie apps for a full month. Includes free-tier usage patterns, Flash vs Pro decision criteria, and cost-minimizing Python code.

Gemini Advanced/2026-05-05Advanced

Putting Gemini 2.5 Flash Thinking Mode to Work: Reading the Cost-Accuracy-Speed Tradeoff

After three months of testing Gemini 2.5 Flash's Thinking Mode on real projects, here's what actually works: which tasks benefit, which tasks waste budget, and how to build a cost-aware switching layer.

Gemini Basics/2026-05-04Advanced

Gemini 3.2 in Production: A Playbook for Model Selection, Cost Optimization, and Implementation Patterns

Gemini 3.2 has plenty of feature coverage, but very little material on actually deploying it to production. This playbook covers model selection (Pro/Flash/Nano), API patterns, cost optimization, competitive comparisons, and operations — from running Gemini across four sites.

Gemini API/2026-05-03Intermediate

Cut Gemini API Costs by 6x with Gemini 2.5 Flash-Lite

Gemini 2.5 Flash-Lite is now stable and generally available. This guide compares pricing against Flash and Pro with real numbers, walks through Python code examples, and explains which tasks are a perfect fit—and which aren't.

Updates/2026-04-11Intermediate

Run Gemma 4 Locally: Building Zero-Cost AI Apps

A complete guide to running Gemma 4 locally and building AI apps with zero API costs. Covers setup on MacBook and Raspberry Pi, production architecture design, and leveraging the 256K context window.

Gemini API/2026-04-02Advanced

How I Cut My Gemini API Bill from ¥52,000 to ¥8,400 a Month — Caching, Model Routing, and the Batch API

A working record of cutting my Gemini API bill from ¥52,000 to ¥8,400 a month. Covers implicit vs. explicit caching, Flash/Pro routing rules, migrating to the Batch API, and a usage_metadata logging setup — with the production code I actually run.

Gemini API/2026-03-24Advanced

Gemini API Context Caching— Cut Document Processing Costs by 90%

Learn how to use Gemini API's context caching to reduce repetitive document processing costs by up to 90%. Includes Python SDK implementation, caching strategies, and cost calculations.

Gemini API/2026-03-21Advanced

Gemini Batch Processing API Guide— Process Thousands of Requests at 50% Off

A comprehensive guide to Gemini's Batch Processing API. Learn how to process thousands of requests asynchronously, cut costs by 50%, and build production-grade batch pipelines with Python and TypeScript.