Modular AI vs Anyscale

By valuation, Modular AI is the larger company at $1.6B versus $1B — a 1.6x difference. Size can also be measured by team: Modular AI employs 150 people while Anyscale has 250 employees.

Modular AI has raised more in total funding at $380M, compared to Anyscale's $281M — a gap of $99M. Combined, the two companies have completed 7 known funding rounds.

Modular AI leads with an Awaira Score of 76/100, while Anyscale sits at 72/100. That 4-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

Modular AI was founded by Chris Lattner in 2022. Anyscale was founded by Robert Nishihara in 2019. Visit each company's profile on Awaira for a full founder biography.

Modular AI: Modular AI, founded in 2022 and valued at $1.6 billion, develops infrastructure software for AI systems. The company has raised $380 million in Series C funding. Modular AI's core focus is building compiler and runtime technologies that optimize AI model execution across diverse hardware platforms. The company's primary product is Mojo, a programming language designed to bridge the gap between research and production AI systems, enabling developers to write performant code without switching between multiple languages. Mojo combines Python's accessibility with systems programming capabilities, targeting the inefficiencies in traditional AI development workflows. The platform addresses a critical pain point in AI infrastructure: the fragmentation between high-level ML frameworks and low-level optimization requirements. Modular AI positions itself within the growing AI infrastructure layer, competing alongside companies focused on model optimization, deployment, and hardware abstraction. The company operates in a competitive landscape that includes established players in compiler technology and emerging AI infrastructure vendors. Modular AI's approach emphasizes developer productivity and hardware portability, allowing AI engineers to optimize code for various accelerators and processors. The company's growth trajectory reflects broader demand for specialized infrastructure solutions as enterprise AI adoption accelerates. Specific customer deployments are not widely disclosed, though the company targets enterprises seeking deployment flexibility and performance optimization. Modular AI develops Mojo, a systems programming language designed to unify AI research and production workflows by eliminating language switching friction. Anyscale: Anyscale is an AI infrastructure company founded in 2019 that develops and commercializes Ray, an open-source distributed computing framework. Ray enables developers to scale Python applications from laptops to clusters, addressing the computational demands of machine learning workloads. The company provides both open-source Ray and commercial offerings, including Ray Cloud, a managed platform for running distributed AI applications. Anyscale's technology stack focuses on simplifying distributed computing for data scientists and ML engineers who lack distributed systems expertise. Ray supports tasks like hyperparameter tuning, reinforcement learning, and large-scale model training. The framework has gained adoption across organizations building production AI systems. The company has raised $281 million across multiple funding rounds, achieving a $1.0 billion valuation as of its Series C stage. This positions Anyscale within the competitive AI infrastructure market alongside companies addressing similar distributed computing challenges. Anyscale's competitive positioning centers on Ray's ease of use compared to traditional distributed computing frameworks. The open-source community contribution has driven adoption, while the commercial platform generates recurring revenue. The company operates in a growing sector as organizations increasingly require scalable infrastructure for large language models and complex AI workloads. Anyscale monetizes an influential open-source framework by offering managed services and enterprise support to organizations scaling AI applications.

Anyscale got there first, launching in 2019 — that's 3 years of extra runway. Modular AI didn't arrive until 2022. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

Modular AI has about 150 employees; Anyscale has about 250. A bigger team usually means more revenue or heavier VC backing, but in AI, small teams can build at massive scale.

Yes — they're direct rivals. Both Modular AI and Anyscale compete in AI Infrastructure, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.