Google Cloud Next 2026: TPU 8-series launched for the ‘agentic AI’ era

As AI evolves, Google is moving away from 'one-size-fits-all' hardware. Instead, it has designed two separate chips to handle two distinct parts of AI work:

• TPU 8t (training chip): This is optimized for training the world's most complex AI models. According to Google, it can connect up to 9,600 chips like a giant super-machine. It offers three times more processing power than the previous generation and is twice as energy-efficient. It's designed to make the "brains" of AI faster than ever before.
• TPU 8i (inference chip): This chip is responsible for actually running AI and responding to users. Google claims this chip delivers 80% better "performance per dollar," meaning companies can run millions of AI agents simultaneously without spending a fortune. Its speed makes AI agents think and react like real-time assistants.

Although Nvidia's GPUs are still considered the "gold standard" for AI, Google believes it has a significant advantage. Unlike Nvidia, which only manufactures chips, Google builds everything in-house—designing the chips, writing the AI ​​models (like Gemini 3), and owning the massive data centers where these chips run.

This "full-stack" approach allows Google's hardware and software teams to work together and perfectly tune the chips to Google's specific AI code.

Google Chief Scientist Jeff Dean said in an interview, "It now makes more sense to specialize chips for training or inference." By distributing the workload, Google wants to reduce the response time that makes current chatbots feel slow.

The market is changing. While Nvidia recently licensed technology from Groq to speed up its chips, Google has already secured major contracts:

• Meta (Facebook/Instagram): The social media giant has signed a multi-billion-dollar deal to use Google's TPUs for several years. Santosh Janardhan, Meta's infrastructure head, said, "It looks like it could have inference advantages," though he also noted that any new platform comes with some challenges and a learning curve.
• Anthropic: One of the most renowned AI developers has gained access to 1 million TPUs to build its next-generation models.

It's worth noting that Google isn't completely abandoning Nvidia. Recognizing that customers need options, Google Cloud will continue to offer a variety of options, including its Axion CPUs, new TPUs, and even the latest Nvidia GPUs.

However, with the launch of the 8-series, Google has made its intentions clear: when it comes to the future of AI agents, they want to be the leader providing the foundation for the entire industry.