Modal

Modal reports more than $300M annualized revenue after fivefold growth and production use across reinforcement learning, inference, robotics, molecular design, agents and media workloads.

Modal reports more than $300M annualized revenue after fivefold growth and production use across reinforcement learning, inference, robotics, molecular design, agents and media workloads.

Modal surpassed $300M in annualized revenue after growing fivefold since September 2025, reflecting rapid production adoption of its serverless GPU and AI infrastructure across inference, training, fine-tuning and compute-intensive workloads.

Modal built an AI-native cloud runtime with a custom container runtime, image system and GPU scheduler, unifying low-latency inference, multi-node training, reinforcement-learning rollouts and secure agent sandboxes while elastically routing workloads across 20+ clouds.

Modal develops a cloud purpose-built for AI with elastic inference, dynamic agent runtimes, reinforcement learning, massive batch compute and sandboxed execution.

Modal develops a cloud purpose-built for AI with elastic inference, dynamic agent runtimes, reinforcement learning, massive batch compute and sandboxed execution.

Modal raised $355M at a $4.65B valuation in 2026 and has scaled a high-growth AI cloud supporting demanding production workloads.

Modal raised $355M at a $4.65B valuation in 2026 and has scaled a high-growth AI cloud supporting demanding production workloads.

Modal raised $355M in Series C financing at a $4.65B post-money valuation after growing fivefold since September 2025 and surpassing $300M in annualized revenue, with backing from General Catalyst, Redpoint, Menlo, Bain Capital Ventures and Accel.

Modal engineers and operates its own filesystem, container runtime, scheduler and image builder while serving inference, fine-tuning, computational biotech and media workloads across CPUs/GPUs; this spans cloud systems, distributed compute, ML infrastructure and applied AI domains.

Distributed systems, GPU infrastructure, inference, RL, sandboxes and agent runtime skills transfer exceptionally broadly across AI infrastructure employers.

Distributed systems, GPU infrastructure, inference, RL, sandboxes and agent runtime skills transfer exceptionally broadly across AI infrastructure employers.