Modal tops $1B annualized run rate and raises $750M Series D
AI infrastructure company Modal says it has crossed $1B in annualized run rate and raised a $750M Series D at a $15.75B post-money valuation. Accel led the round, according to the company.
- Modal says it crossed $1B in annualized run rate, with usage tripled in five months and growth above 15x year-over-year.
- It raised a $750M Series D at a $15.75B post-money valuation, led by Accel with Kleiner Perkins joining.
- Sandboxes are a $300M run rate product, with close to 3 billion sandboxes spun up.
- Virtual machines are now generally available with Sandboxes, and multi-node training has launched.
- Modal runs on a capacity pool spanning 20+ clouds and has 200+ employees.
Rapid growth since the Series C
Modal says demand has kept accelerating since its Series C, which it announced five months ago. According to the company, usage has tripled since then and it has grown more than 15x year-over-year. The company says it recently passed $1B in annualized run rate and sees no sign of slowing down.
The new $750M Series D values Modal at $15.75B post-money. Accel led the round and Kleiner Perkins joined. All existing investors took part, including Menlo Ventures, General Catalyst, Redpoint, Lux Capital and Bain Capital Ventures. Modal says it has a team of 200+ across NY, SF and Stockholm and is hiring.
Who is building on Modal
Modal points to a wide range of customers. TypeSafe AI's Jev, described by Modal as one of the fastest-growing products ever, served 1T tokens on Modal in its first three days. DoorDash's AI platform team uses Modal to move apps across the company from experiment to production.
- Cognition, Ramp, Linear and Hebbia are building background agents.
- Runway is generating video in every region of the world.
- Physical Intelligence, Generalist AI and 1X are training robots.
- Chai Discovery and Achira run drug discovery on Modal, as do scientists working through Claude Science.
A rebuilt stack and new building blocks
Modal argues that AI workloads do not fit the old infrastructure stack. In the company's words, GPUs are scarce, models are large and slow to load, and code written by LLMs has to run in isolation. Building for this on older tools, it says, leads to "YAML hell and GPU procurement purgatory."
Its response was to replace most of the existing stack. Modal says it built its own file system, container runtime, scheduler and networking from the ground up, on a capacity pool that now spans 20+ clouds.
Functions were its first building block: developers write code and Modal runs it. Modal lists uses such as image generation with diffusion models, music at Suno, LLM inference with vLLM and SGLang, and model training. Sandboxes launched in 2023, and the company says they are now a $300M run rate product on their own. It reports close to 3 billion sandboxes spun up, scaling to a million concurrent.
New products and what comes next
Modal says it recently launched multi-node training, where one decorator gives a fully RDMA-connected cluster with no capacity commitment. It is also moving into reinforcement learning and post-training products. On inference, it has been launching Modal servers for HTTP servers, plus LLM serving features such as Endpoint Candidates. Virtual machines are now generally available with Sandboxes.
The funding is meant to support this expansion. For developers, the pitch is composable, general-purpose infrastructure for AI applications without managing GPUs and containers themselves. The figures are company-reported, and the source does not give independent verification.
