Modal to run AI agent sandboxes on Nvidia's Arm-based Vera CPU, citing 2x throughput
Modal said in a blog post that it plans to run its Sandboxes product — isolated machines where AI agents execute code — on Nvidia's Arm-compatible Vera CPU, its first move away from x86 chips after relying exclusively on Intel and AMD processors. In Modal's own tests, built on a 50-task agentic coding benchmark, Vera handled up to twice as many concurrent tasks as an Intel server as containers were packed more densely, a result Modal credits to high memory bandwidth; the company says the benchmark has not been independently checked. Modal, which raised $750 million led by Accel at a $15.75 billion valuation, said it will keep Intel and AMD chips in a hybrid fleet and did not say when Vera-powered sandboxes would reach customers.
The deal is an early sign that Nvidia's standalone Vera CPU, unveiled in March with 88 cores and already named for Anthropic and OpenAI, can win business in the server CPU market long dominated by Intel and AMD — though Modal's 2x figure remains an unverified vendor benchmark.
Last week, NVIDIA hand-delivered Modal’s first Vera CPU server to our SF office. It’s now purring away in a server rack, and we’re pretty excited about what it could mean for Modal Sandboxes and, consequently, Modal users.
Vera is NVIDIA’s new Arm-compatible CPU, built for the Vera Rubin GPU platform but also available as a standalone CPU server.
Supporting Arm would be a huge change for Modal, coming from a long history exclusively running x86 machines. We’d need to make changes across our infrastructure and image build system to support an entirely different CPU architecture, but the benchmarks are impressive: a 2x increase on throughput. With this, the NVIDIA Vera CPU becomes an incredibly compelling option for powering Modal Sandboxes.
Why Vera could be a big deal for Modal
Firstly, multi-tenant clusters are noisy.
Orchestration for a Sandbox product means running hundreds of concurrent containers and VMs on each cloud host. Unlike normal Kubernetes server deployments colocating pods on the same host, the shape of each sandbox workload is unique, and it leads to some interesting dynamics within a multi-tenant cluster:
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