CoreWeave to Power Wayve's AI Driver Training in Multi-Year Agreement

Wayve’s multi-year commitment covers cloud infrastructure for autonomous-driving model training, evaluation and simulation.

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Wayve will train its end-to-end foundation models on CoreWeave Cloud, expanding training and evaluation as it accelerates commercial deployment for autonomous vehicles

LIVINGSTON, N.J.--(BUSINESS WIRE)-- CoreWeave, Inc. (Nasdaq: CRWV), The Essential Cloud for AI®, today announced a multi-year agreement with Wayve, the global leader in embodied intelligence building the AI Driver for autonomous vehicles. Wayve will train its foundation models on CoreWeave Cloud with NVIDIA Blackwell GPUs, expanding its AI infrastructure for training, evaluation, and simulation. Wayve began using Weights & Biases and has now scaled into leveraging CoreWeave Cloud.

Wayve’s AI Driver is becoming the driving intelligence layer the automotive industry is choosing to build on, from personally-owned cars to robotaxis. It learns to drive from real-world data collected in more than 70 countries, which makes it a frontier training workload with physics and safety attached. Models of that kind demand purpose-built cloud solutions, with reliability across long training runs and enough observability to prove one version is better than the last and validate safety at scale.

"Our AI Driver gets better by running this data flywheel: gathering real-world driving experience, training on it, evaluating it, and deploying only what outperforms what is already on the road," said Silvius Rus, SVP of Engineering at Wayve. "Being able to access CoreWeave’s AI cloud, purpose-built for workloads like ours, helps accelerate the commercial deployment of our AI Driver."

"This agreement brings one of the most demanding physical AI programs in the world onto a platform purpose-built for it," said Gavin Jackson, managing director, EMEA, CoreWeave. "As AI moves from the screen into the physical world, the companies leading that shift need training, evaluation, and simulation infrastructure designed to work together from the start."

CoreWeave consistently delivers industry-leading performance, demonstrated by record-breaking MLPerf benchmark results in inference and training, its position as the only AI cloud to earn the top Platinum ranking in SemiAnalysis ClusterMAX™ three times in a row, and its #1 ranking for inference speed and price-performance for Moonshot AI’s Kimi K2.6 and Kimi K2.7 Code in independent inference benchmarking conducted by Artificial Analysis.

About CoreWeave

CoreWeave is The Essential Cloud for AI®. Built for pioneers by pioneers, CoreWeave delivers a fully integrated platform of technology and teams that enables innovators to move at the pace of innovation, building and scaling AI with confidence. Trusted by 9 of the 10 leading foundation model providers, CoreWeave serves as a force multiplier by combining superior infrastructure performance with deep technical expertise to accelerate human discovery. Established in 2017, CoreWeave completed its public listing on Nasdaq (CRWV) in March 2025.

About Wayve

Founded in 2017, Wayve is the leading developer of Embodied AI technology. Its advanced foundation models and AI software for autonomy enable machines to perceive, understand, and navigate any environment. Wayve's first application is automated driving, developing a mapless and hardware-agnostic “AI Driver” for automakers and fleet owners to accelerate the path from assisted to automated driving on any vehicle, anywhere. Backed by top investors like SoftBank Group, NVIDIA, Uber, and Eclipse Ventures, Wayve's mission is to reimagine mobility — and beyond — with embodied intelligence. To learn more, please visit www.wayve.ai.

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Media Contact
press@coreweave.com

Source: CoreWeave, Inc.

Key Terms

foundation models technical

Foundation models are very large artificial intelligence systems trained on broad, general data so they can be quickly adapted to many different tasks, like a powerful, general-purpose engine or a Swiss Army knife for software. They matter to investors because they can lower costs and speed innovation across industries, create new products or revenue streams, and change competitive dynamics, while also introducing operational and regulatory risks that can affect a company’s financial outlook.

observability technical

Observability is a company’s ability to see and understand what its software systems are doing by collecting and analyzing signals like logs, metrics and traces. For investors it matters because strong observability reduces the risk of downtime, hidden bugs or security issues, supports faster fixes and efficient scaling, and therefore can protect revenue, lower costs and signal disciplined operations — like having clear gauges and alarms on a complex machine.

inference technical

Inference is the process of drawing a conclusion from available evidence or data, like a detective piecing together clues to form a likely story. For investors it matters because these judgments turn raw reports, test results, or market signals into expectations about future performance, risk, or regulatory outcomes—so how someone infers from the same facts can change investment decisions and valuation.