Neoclouds have staked their claim to AI compute infrastructure with low-cost GPU-based alternatives and purpose-built features for AI training and inference. But can this new class of alternative clouds actually take business from the hyperscalers?
Some argue that neoclouds are poised to capture a growing share of AI-native workloads. Neocloud revenue exceeded $25 billion in 2025, reports Synergy Research Group. And Gartner predicts neoclouds could take 20% of the $267 billion AI cloud market by the year 2030.
“Neoclouds offer purpose-built, NVIDIA-native infrastructure optimized for AI, with InfiniBand networking, bare-metal access, and lower costs,” says Hardeep Singh, senior principal analyst at Gartner. “They focus on high-performance GPU clusters and flexible contracts, unlike hyperscalers’ general-purpose, legacy-heavy platforms.”
There are over 100 neoclouds in the market today, yet only 10 or 15 are operating at a “meaningful scale” in the United States, reports global consultancy McKinsey & Company. But while the neocloud category is growing, there is little evidence that a large percentage of enterprises have standardized upon neoclouds to date.
What are neoclouds?
