At this year's Google I/O conference, Google CEO Sundar Pichai shifted the conversation around artificial intelligence to focus on economics. Pichai warned that companies worldwide are exhausting their annual AI budgets by May due to runaway token usage. He noted that the rapid rise of AI agents has created unprecedented costs for enterprises. "Companies are already blowing through their annual token budgets, and it's only May," Pichai said, referring to the billions of tokens consumed by AI systems each month.
Gemini 3.5 Flash: A Cost-Saving Solution
To address these soaring costs, Pichai unveiled Gemini 3.5 Flash, a model designed to rival frontier offerings while significantly cutting expenses. He stated that companies could save over $1 billion annually if they shifted 80% of their workloads to a mix of Flash and other frontier models. "If companies used a mix of Flash and other frontier models, they could save a lot of money. To put this in perspective, top companies are processing about 1 trillion tokens a day. If they shifted 80% of their workloads from other frontier models to 3.5 Flash, they'd save over $1 billion dollars annually. That is real savings they can pour back into their company," added Pichai.
What Is Gemini 3.5 Flash?
Google unveiled Gemini 3.5 Flash, its latest AI model, at the I/O 2026 developers conference. The company has positioned this model as the first release in the new Gemini 3.5 family. The AI model is designed to deliver improved performance for coding, agentic AI tasks, and multimodal understanding while maintaining the faster response speeds associated with the Flash series.
According to Google, Gemini 3.5 Flash is now available globally through the Gemini app, AI Mode in Search, Google AI Studio, Android Studio, and enterprise platforms. The model also powers new AI experiences across Google products, including the upcoming Gemini Spark personal AI agent.
The company stated that Gemini 3.5 Flash performs better than Gemini 3.1 Pro across several coding and agentic benchmarks, including Terminal-Bench 2.1, GDPval-AA, and MCP Atlas. Google added that the model can handle long-horizon workflows, enabling it to execute multi-step tasks such as application development, code maintenance, and document preparation.
Google also highlighted improvements in multimodal capabilities, stating that Gemini 3.5 Flash can generate interactive web interfaces, graphics, and animations while supporting more complex reasoning tasks. The model is designed to work with Google's updated Antigravity platform, allowing multiple AI subagents to collaborate on larger workflows.
Why Google Has an Edge
Google's advantage lies in owning the full stack: chips, data centers, cloud, models, and applications. Analysts estimate that Google pays 50% to 75% less for AI compute than rivals, thanks to its custom TPU chips and direct sourcing. By contrast, competitors like OpenAI rely on Microsoft, Oracle, and Nvidia, paying margins at every layer of infrastructure.
This article was contributed by the TOI Tech Desk, a dedicated team of journalists committed to delivering the latest and most relevant news from the world of technology to readers of The Times of India. Their coverage spans gadget launches, reviews, trends, in-depth analysis, exclusive reports, and breaking stories that impact technology and the digital universe.
