By PYMNTS | October 14, 2026
Artificial intelligence (AI) infrastructure startup Modal was valued at $15.75 billion in a Series D funding round in which it raised $750 million, CEO Erik Bernhardsson said in a Wednesday (Oct. 14) blog post.
Modal’s new valuation is more than triple the $4.65 billion valuation the company achieved in a May Series C round in which is raised $355 million.
“Just five months ago, when we announced our Series C, I wrote that demand was accelerating,” Bernhardsson said in the Wednesday post. “Since then, usage has tripled and we’ve grown more than 15x year-over-year. We recently crossed $1B in annualized run rate with no sign of slowing down.”
Modal provides a platform for production AI, with cloud infrastructure for teams that develop, train and serve AI applications at scale. The company’s offerings span inference, training, sandboxes and functions, according to its website.
Companies use the Modal platform to get apps from experimentation to production, to build agents, to generate lifelike video, to train robots and to run drug discovery, according to the post.
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“A new world of software capabilities requires a new set of building blocks and we’re just getting started,” Bernhardsson said in the post.
With the new capital, Modal will “keep building what’s next,” Bernhardsson said.
Modal’s latest funding round was led by Accel, per the post.
Accel said in a Wednesday blog post that the infrastructure to train, serve and run AI is the fastest growing market in technology. Plus, the industry is only in the very early stages of building that infrastructure, per the post.
“As the market evolves from ‘AI-natives’ to every company using AI tools, Modal provides the building blocks for the smallest startups to the largest companies in the world,” Accel’s Rich Wong and Gonzalo Mocorrea said in the post.
PYMNTS reported in September 2025 that inference infrastructure is the next big layer in the generative AI tech stack because latency, cost, scale, energy use and deployment location all determine whether an AI service works or fails.
The report said that investors were already rewarding firms that capture inference demand, and that enterprises deploying generative AI solutions face inference costs that can reach hundreds of millions annually.