Modal Labs nears $750M funding round at $16B valuation
The AI infrastructure startup's valuation has more than tripled in roughly four months, riding a wave of explosive revenue growth fueled by demand for AI coding tools and inference capacity.
Modal Labs, the serverless AI infrastructure company founded in 2021, is in talks to raise new funding at a valuation approaching $15 billion. That would represent more than a threefold jump from the $4.65 billion post-money valuation the company commanded after closing its $355 million Series C just four months ago in May 2026.
Revenue growth that explains the hype
Modal’s annualized revenue surged from approximately $60 million in September 2025 to nearly $300 million by May 2026. That’s roughly a fivefold increase in under nine months.
The growth has been driven primarily by surging demand for AI coding tools and inference workloads, the computational tasks required to actually run trained AI models in production.
Modal’s platform handles the essential plumbing: it lets developers run Python functions and AI workloads on GPUs and CPUs across more than 13 cloud providers without having to manage the underlying infrastructure themselves. The company says it has launched more than 1 billion sandbox environments to date.
From seed round to potential decacorn
Modal raised $7 million in seed funding in early 2022, followed by a $16 million Series A in October 2023. Its $87 million Series B in September 2025 valued it at $1.1 billion. Then came the $355 million Series C in May 2026 at $4.65 billion.
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Co-founders Erik Bernhardsson and Akshat Bubna have attracted backing from prominent venture firms including Redpoint Ventures and General Catalyst. Bernhardsson previously led the machine learning team at Spotify.
A crowded but well-funded competitive landscape
Baseten, a competitor that also provides infrastructure for deploying and scaling machine learning models, has reached a valuation of approximately $26 billion, illustrating just how much capital is chasing this category.
Modal’s serverless approach, where developers pay for compute only when their code is actually running rather than reserving capacity around the clock, aligns with how many AI workloads actually behave. Inference tasks tend to be bursty and unpredictable, making traditional reserved-instance cloud computing both expensive and inefficient.