When Will TOPS Beat MPH

In December, Rivian made an unexpected announcement.

Rivian Founder and CEO RJ Scaringe told a room full of reporters and investors that they planned to design their own silicon and autonomous driving computer system, the Rivian Autonomy Processor and Gen 3 Autonomy Computer.

Their silicon would be capable of around 1600 TOPS.

TOPS stands for Trillions of Operations Per Second (or sometimes Tera Operations Per Second), a metric that measures the performance and speed of AI chips such as NPUs, GPUs, and TPUs.

The better the TOPS, the better the AI processing.

Higher TOPS generally signifies a more capable device for AI tasks like image generation, language modelling, or advanced driver assistance systems (ADAS).

When we’re talking about on-board compute used in cars to make decisions about when your vehicle should turn, accelerate, hit the brakes, or when to drive into a tree (for no good reason), you want all of the TOPS you can get.

Jensen Huang is well aware that TOPS matter.

Last week at Nvidia’s GTC conference, Huang announced that the Nvidia Drive Hyperion platform will underpin upcoming Level 4-capable vehicles from Hyundai, Nissan, Isuzu, BYD, and Geely.

These folks join previously announced OEMs, including Mercedes-Benz, Toyota, and GM.

Drive is Nvidia’s platform for building ADAS, and eventually, fully autonomous cars.

It includes the computers, software, and AI tools that help vehicles perceive the world around them, understand what is happening, and make real-time driving decisions.

Hyperion is the blueprint for building an autonomous driving system using Drive.

One of Nvidia’s selling points is how they’ve accelerated the advancement of higher-level autonomous systems.

They’ve been using deep reinforcement learning (DRL) to train autonomous vehicle agents by allowing them to interact with simulated environments, learning optimal driving practices through virtual trial and error rather than solely relying on labelled datasets and real-world road miles.

The recommended Drive system uses two of Nvidia’s AGX Thor purpose-built in-vehicle computers delivering a combined 2,000 TOPS.

That’s a lot of compute.

Tesla’s current Hardware 4 is estimated to deliver a modest 100–150 TOPS for its Full Self-Driving system.

Elon has compute dreams of his own.

This week, he nerded out on X over his plans for Hardware 5 and their silicon design called AI5, claiming it “will punch far above its weight”.

The AI5 will match or exceed Nvidia’s Drive, expecting to tap out at around 2,500 TOPS.

When will your car drive itself?

Nvidia’s system is already in a handful of cars today. But Jensen still has work to do on the deep learning. Getting up to level-4 autonomy will take a bit more time.

Rivian expects its new chips to be woven into production vehicles by the end of the year.

As for Tesla, well, Elon’s not great with deadlines. AI5 will take a bit longer. Initial AI5 chips were expected in early 2026. Mass production of AI5, manufactured by both Samsung and TSMC, is delayed until mid-2027.

As high-torque, electric, software-developed vehicles become the norm, historical vehicle benchmarks become increasingly irrelevant.

What happens when every vehicle can do 0-60 in under 4 seconds?

ICYMI: Kia and Hyundai already build EVs that outpace many BMW, Lucid and Porsche models on the track.

As hardware components and performance stats for electric vehicles converge, other speed benchmarks will become more of a selling point.

Maybe TOPS will become more important than horsepower, top speeds and miles per hour.

How many TOPS does your car have under the hood?

You might not care today, but you will.

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