The company is making advanced AI tools more accessible in markets where high subscription costs have limited adoption.

The Plus plan, priced at roughly $5 per month in most regions, offers a six-month, 50% discount in selected countries like Nepal and Mexico. It grants users access to Gemini 2.5 Pro, a multimodal AI capable of generating images and videos, alongside integrated productivity features in Gmail, Docs, and Sheets. 

Subscribers also get 200GB of cloud storage and enhanced capabilities within Google’s AI research assistant, NotebookLM, which now supports long-context document analysis, a feature particularly useful for students, researchers, and journalists.

Tools like Flow, Whisk, and Veo 3 Fast are also included. They allow fast creation of animations, visual content, and video assets, directly appealing to the creator economy in regions where mobile-first usage dominates.

The launch comes a day after OpenAI expanded its ChatGPT Go plan to Indonesia, a sub-$5 subscription tier that grants access to GPT-4-turbo but lacks the integrated productivity tools and cloud storage of Google’s Plus tier. 

Analysts see these pricing strategies as a transition from competing on raw AI model power to offering complete ecosystems that integrate seamlessly into daily workflows.

Usage of AI tools in Africa has surged by 240% since 2023, with Nigeria, Kenya, and Egypt leading growth, according to Statista and GSMA. Southeast Asia is witnessing similar trends, particularly in Indonesia and Vietnam, where freelancers and small businesses increasingly adopt AI-powered productivity tools.

India, despite being a top AI market where OpenAI debuted ChatGPT Go, is missing from Google’s rollout. Experts say this may relate to ongoing adjustments in pricing and compliance strategies to address data localisation and regulatory challenges.

Google is making AI affordable without sacrificing utility, especially in emerging markets where a $20 subscription is usually prohibitive. For users in Nigeria and similar economies, the new Google AI Plus plan could be a game-changer.

The new model doesn’t just crunch numbers or regurgitate facts. According to Google, Gemini 2.5 Pro is built to “reason.” That word means more here than just solving logic puzzles.

The company claims it can analyse situations, pull context from messy inputs, make logical decisions, and execute with purpose. That’s a tall order.

From what’s been shared, Gemini 2.5 Pro is an experimental release, and yet it already leads other models. It landed the top spot on LMArena, a win that shows human preferences. In simpler terms, it performs well in ways people actually notice and value. That’s not always the case with models built for lab results.

The model reportedly does great in code, maths, and science. It aced GPQA and AIME 2025—two widely recognised benchmarks in reasoning-heavy domains—and scored 18.8% on Humanity’s Last Exam, a deliberately difficult test created by experts to measure the limits of human-level knowledge.

This isn’t the first time Google has thrown around the term “thinking model.” They’d introduced something similar with Gemini 2.0 Flash Thinking. But this time, the improvements go deeper. The base model has been reworked. 

Post-training has been upgraded. And if Google follows through, all future models will come with these “thinking” upgrades baked in.

What’s more, Gemini 2.5 Pro is already available for use in Google AI Studio and the Gemini app, although only for those subscribed to the Gemini Advanced tier. Google promises that wider availability on Vertex AI is coming, and pricing will be rolled out soon, allowing users to scale production with higher usage limits.

As for what this means in practical terms—well, it depends on who you ask. To developers, this might be a tool that can write cleaner code or solve engineering problems with more context. To businesses, it’s potentially a strategic advantage in automation and decision-making. For the average user? That’s less clear.

In all the noise about benchmarks, one line stood out: “We’re building these thinking capabilities directly into all of our models, so they can handle more complex problems and support even more capable, context-aware agents.”

That’s the direction. Not just faster answers. Smarter ones.

But of course, we’ve heard that before. Whether Gemini 2.5 meets our expectations won’t be decided by a leaderboard. It’ll be decided by what people build with it—and how much they trust it to think.