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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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Gemini in March 2026 — Monthly Highlights and What to Watch Next

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A Month That Reshaped the AI Landscape

March 2026 was nothing short of transformative for Google Gemini. The official launch of the Gemini 3.1 Pro and Flash models, surpassing 750 million monthly active users, and the bold introduction of a ChatGPT chat history import tool — each week brought announcements that shifted the competitive landscape.

At Gemini Lab, we published over 270 articles this month covering everything from beginner guides to production-grade API architectures. In this monthly roundup, we'll walk through the biggest developments, highlight the most popular articles on the site, and look ahead to what April has in store.

Key Updates This Month

Gemini 3.1 Pro and Flash Go Official

The headline story of March was the official release of the Gemini 3.1 series. Gemini 3.1 Pro delivered significant improvements in reasoning accuracy for complex tasks, and the new gemini-3.1-pro-preview-customtools endpoint now allows developers to combine bash tools with custom Function Calling in a single API call.

On the Flash side, as we covered in Gemini 3.1 Flash High-Speed API Implementation Techniques, streaming and batch processing optimizations have matured to the point where Flash is a serious contender for production workloads.

Gemini 3.1 Flash-Lite — The Most Cost-Effective Model Yet

Launched on March 3rd, Flash-Lite set a new bar for affordability at $0.25 per million input tokens and $1.50 per million output tokens. Compared to Gemini 2.5 Flash, it achieves 2.5x faster time-to-first-token and 45% higher output throughput. For high-volume production workloads, this is a game-changing price-to-performance ratio.

ChatGPT and Claude Chat History Import

Announced on March 26th, this feature sent ripples across the AI industry. Users can now export their conversation logs from ChatGPT or Claude as a .zip file and upload them to gemini.google.com/import, seamlessly carrying over their chat history.

The companion "Memory Import" feature is even more interesting: paste a special prompt into your current chatbot, have it generate a summary of everything it knows about you, then import that summary into Gemini. From day one, Gemini already "knows" your preferences, work context, and communication style — no weeks of onboarding needed.

Google AI Studio Gets a Major Overhaul

The mid-March AI Studio redesign introduced a unified playground where developers can work with Gemini, GenMedia (powered by Veo 3.1), text-to-speech, and Live models — all without switching tabs. This end-to-end prototyping environment makes it significantly faster to iterate on multimodal AI applications.

The update also introduced the ability to combine built-in tools with custom Function Calling in a single API call, dramatically expanding what's possible without stitching together separate workflows.

Workspace Integration Levels Up

On March 10th, Google rolled out enhanced Gemini capabilities across the entire Workspace suite. Gemini in Docs now assists with drafting and editing, Sheets handles data analysis and formula generation, Slides enables AI-driven presentation design, and Drive answers complex questions by searching across files and emails.

We covered these features in depth in our guides to Gemini × Google Sheets AI Workflows and Google Slides × Gemini AI Presentation Design.

750 Million Monthly Active Users

Google confirmed in March that Gemini surpassed 750 million monthly active users — more than doubling the estimated 350 million at the end of 2025. The rapid growth is fueled by native integration into Android and Pixel devices, deeper Workspace connectivity, and expansion into Google TV and Home devices.

Most Popular Articles This Month

Here are the five articles that resonated most with Gemini Lab readers in March.

1. Gemini 3.1 Pro Complete Guide — A comprehensive reference covering every feature, API parameter, and migration step for 3.1 Pro. Essential reading for developers planning their upgrade path.

2. Gemini API × Python Automation Recipes — Copy-paste-ready Python snippets for text summarization, image analysis, batch processing, and more. Practical and immediately useful.

3. Gemini vs GPT-5.4 In-Depth Comparison (2026) — The definitive side-by-side comparison of cost, speed, and accuracy to help you pick the right model for your use case.

4. Google ADK vs LangChain Framework Comparison — A hands-on comparison of the two leading AI agent frameworks, complete with implementation examples.

5. Gemini Deep Think × Adaptive Thinking Strategy — Advanced techniques for intelligently routing between reasoning models to cut API costs by up to 50%.

Reflections on the Month

The overarching theme of March was convergence. For a long time, the Gemini API, Google AI Studio, Workspace, and Android felt like separate product lines evolving independently. This month's updates began dissolving those boundaries at remarkable speed.

Prototype in AI Studio, integrate into Workspace for daily operations, deploy as an agent on Android — this seamless workflow is no longer aspirational. It's becoming the default way to build with Gemini. For developers, the value of understanding the Google AI ecosystem holistically has never been higher.

At Gemini Lab, we'll be expanding our coverage in April to include more cross-ecosystem practical guides that connect these pieces together.

What to Watch in April

Gemini 3.1 Pro GA and Model Consolidation

With 3.1 Pro currently in preview, a general availability (GA) release in April is highly anticipated. GA status brings SLA guarantees and enterprise-grade support, making it safer for production deployments. Expect a deprecation timeline for 3.0 series models to accompany the announcement.

Gemini CLI Stabilization

March's nightly updates added customizable keyboard shortcuts, Vim mode improvements, and tool sandboxing to Gemini CLI. April should see these features land in a stable release. We'll keep our Gemini CLI guide updated as changes roll out.

Google I/O 2026 Pre-Announcements

With Google I/O typically held in May, April is when pre-announcement activity ramps up. Expect previews of new multimodal capabilities, expanded agent frameworks, and potentially new Enterprise tier offerings for Gemini.

Apple × Gemini Partnership Details

The Apple × Google Gemini partnership reported in March is expected to reveal more concrete details in April. The possibility of Gemini distilled models running on-device on iOS could be a watershed moment for mobile developers.

Summary

March 2026 saw Gemini advance on three fronts simultaneously: model evolution (3.1 Pro, Flash, and Flash-Lite), ecosystem integration (Workspace, Android, and Google TV), and user acquisition strategy (chat history import and 750 million users). It was one of the most consequential months in Gemini's history.

Gemini Lab will continue delivering timely coverage of the latest updates alongside practical API tutorials and developer guides. April promises to be just as exciting — stay tuned.

For a deeper dive into the topics covered in this article, we recommend "Google Gemini: The Complete Guide" for a systematic exploration of Gemini API fundamentals and advanced techniques.

Frequently Asked Questions

Q: What are the key differences between Gemini 3.1 Pro and 3.0 Pro?

A: Gemini 3.1 Pro improves reasoning accuracy and introduces a new endpoint that supports simultaneous use of custom tools and bash tools. Token processing speed and context window efficiency have also been improved, resulting in significantly better production performance.

Q: In which regions is the ChatGPT history import available?

A: As of late March 2026, the feature is available in most regions except the EEA (European Economic Area), Switzerland, and the United Kingdom due to local data regulations. Expansion to additional regions is expected in the coming months. You can access the import tool at gemini.google.com/import.

Q: What's the single most important thing to watch for in April?

A: The general availability (GA) release of Gemini 3.1 Pro is the biggest milestone to watch. GA status brings SLA guarantees and makes the model suitable for mission-critical production deployments. Also keep an eye on pre-announcements ahead of Google I/O 2026.