Modal, the AI infrastructure platform developers use to train and run models without managing servers, has raised $750 million in a Series D round at a $15.75 billion post-money valuation — more than triple its valuation from just five months ago. Why it matters: investors are paying up fastest for the plumbing underneath AI agents, and Modal says that demand has already pushed it past $1 billion in annualized run rate.
October 14, 2026
What happened
Modal announced the Series D on Wednesday, October 14. Accel led the round, Kleiner Perkins joined, and all of the company’s existing investors took part, including Menlo Ventures, General Catalyst, Redpoint, Lux Capital, Amplify Partners and Bain Capital Ventures. The raise follows a $355 million Series C in May that valued Modal at $4.65 billion, so the company’s price tag has more than tripled in roughly five months.
The growth Modal is reporting
The valuation jump rests on numbers Modal itself reported alongside the raise. The company says it recently crossed $1 billion in annualized run rate, that usage has tripled since the May round, and that it has grown more than 15 times year over year. Its Sandboxes product — isolated containers where developers, and increasingly AI agents, can run code — accounts for about $300 million of that run rate on its own, according to the company, which says it has spun up close to 3 billion sandboxes and can scale to a million running at once. Treat those as company-reported figures rather than audited results, but the direction is consistent with what other infrastructure startups are seeing.
What Modal actually sells
Modal rents out cloud infrastructure packaged for AI work: inference, training, sandboxes and functions that let teams move from experiment to production without running their own GPU fleets. Workloads on the platform include building agents, generating video, training robots and running drug discovery, per the company. Recent additions include multi-node training on RDMA-connected clusters with no capacity commitment, new HTTP serving through Modal servers, an inference feature called Endpoint Candidates, virtual-machine sandboxes now generally available, and a push into reinforcement learning and post-training products.
Why it matters
Every AI agent needs somewhere safe and fast to execute code, and that execution layer is turning into one of the most contested — and best funded — parts of the stack. Modal’s pitch is that the next generation of software will need entirely new building blocks, and it wants a lot of that software to run on its platform. The practical take for builders: sandbox and inference capacity is getting cheaper to rent and easier to scale, but the vendors providing it are consolidating fast and raising at valuations that assume agent workloads keep compounding. At Tested Intelligence — everything AI, tested — we read a $750 million round five months after the last one as a demand signal, not just a funding headline.
Frequently asked questions
How much did Modal raise, and at what valuation?
Modal raised $750 million in a Series D round at a $15.75 billion post-money valuation, led by Accel with Kleiner Perkins and all existing investors participating.
How fast is Modal growing?
By the company’s own reporting, it has passed $1 billion in annualized run rate, usage has tripled since May 2026, and growth is more than 15 times year over year.
What is Modal used for?
Developers use Modal to train and serve AI applications at scale — inference, training, sandboxes for running agent-generated code, and functions — including workloads such as video generation, robot training and drug discovery.
Sources: Modal, SiliconANGLE, PYMNTS