Modal crosses $1B in Annualized Run Rate and raises $750M Series D

Modal reports that its usage has tripled since its Series C announcement five months earlier, with more than 15-fold year-over-year growth and over $1 billion in annualized run rate. The company argues that AI applications require infrastructure beyond traditional cloud tools because of scarce GPUs, large and slow-loading models, and the need to run AI-generated code in isolated environments; it has therefore built its own filesystem, container runtime, scheduler, and networking across capacity in more than 20 clouds. Modal says customers including DoorDash, Cognition, Ramp, Runway, robotics firms, and drug-discovery organizations use its platform for AI deployment, inference, video generation, robotics training, and scientific work. Its core products include Functions for executing code and Sandboxes for isolated code execution, which it says have reached a $300 million run rate, nearly 3 billion launches, and capacity for one million concurrent instances. The company is also expanding into multi-node training, reinforcement learning and post-training tools, HTTP servers, LLM-serving features, and generally available virtual machines, supported by a new $750 million Series D led by Accel at a $15.75 billion post-money valuation.

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