Seventeen US-based AI companies have raised $100 million or more in funding during 2026, with three securing rounds exceeding $1 billion. The data, compiled as of February 17, highlights the concentration of capital in a small number of frontier AI companies while mid-stage startups compete for a shrinking share of available venture funding.
OpenAI leads the cohort with a $110 billion Series C round closed in February 2026, pushing the company’s valuation to $840 billion as of March 11. Anthropic followed with a $30 billion Series G round in the same month. These two raises alone account for the majority of total AI funding in 2026, underscoring the degree to which the frontier model market has consolidated around a handful of companies with the capital requirements and revenue trajectories to justify nine- and ten-figure investments.
The remaining 14 companies in the $100 million-plus category span infrastructure, enterprise applications, and vertical AI solutions. This tier includes companies building GPU cloud infrastructure, AI-powered development tools, healthcare AI platforms, and autonomous systems — segments where investors see defensible market positions and clear paths to revenue. The common thread is that each company addresses a specific enterprise need where AI delivers measurable ROI, rather than competing directly with OpenAI or Anthropic on foundation models.
The funding concentration has implications for the broader AI startup ecosystem. With OpenAI and Anthropic absorbing $140 billion between them, the remaining venture capital available for earlier-stage AI companies is constrained. Seed and Series A rounds for AI startups have become more competitive, with investors demanding clearer differentiation from foundation model providers and more concrete evidence of product-market fit before committing capital.
The $100 million threshold itself has shifted in meaning. In 2023, a $100 million AI round was exceptional. In 2026, it represents the minimum scale required to build and maintain competitive AI infrastructure — the compute costs for training, the engineering teams for deployment, and the sales organizations for enterprise distribution have all inflated to the point where sub-$100 million raises limit a company’s ability to compete at the frontier.
