Lambda vs Snowflake
Side-by-side comparison of AI visibility scores, market position, and capabilities
San Jose AI GPU cloud "Superintelligence Cloud" at $500M revenue run rate May 2025; $2.5B+ total ($1.5B TWG Global Series E Nov 2025) serving Apple/Microsoft/DoD/Stanford with B200/H100 clusters competing with CoreWeave for AI training infrastruct...
About
Lambda (Lambda Labs) is a San Jose, California-based AI cloud infrastructure provider — backed with $2.5+ billion in total funding including a $1.5 billion Series E in November 2025 led by TWG Global and USIT, a $480 million Series D at a $4 billion valuation in February 2025, and a $320 million Series C in 2024 — providing AI researchers, enterprises, and startups with on-demand GPU cloud computing infrastructure for AI model training and inference, serving customers including Apple, Microsoft, Tencent, the Department of Defense, MIT, Stanford, Harvard, and Caltech. Lambda's revenue run rate reached $500 million in May 2025 (up from $425 million in December 2024), driven by a multi-billion dollar partnership with Microsoft and surging enterprise AI training demand. Founded in 2012 by brothers Stephen and Michael Balaban (originally a facial recognition startup, pivoted to GPU cloud in 2017).
Cortex AI platform for enterprise LLM deployment within the data cloud; $900M+ ARR from AI/ML workloads. AI Data Cloud serves 10,000+ enterprise customers. Cortex Analyst, Cortex Search enable natural-language querying of enterprise data.
About
Snowflake was founded in 2012 by data warehousing veterans from Oracle with the mission of building a data platform designed from scratch for the cloud — one that separated compute from storage to enable elastic scaling, multi-cloud portability, and a consumption-based pricing model that aligned cost with actual use. The company identified that legacy data warehouses required customers to over-provision hardware for peak demand, creating enormous waste, and that the emerging cloud infrastructure layer made a fundamentally different architectural approach possible. Snowflake's core technology, the Data Cloud, provides a single platform for data warehousing, data lakes, data engineering, data science, and data sharing across AWS, Azure, and Google Cloud.\n\nSnowflake's platform has expanded beyond structured analytics into an AI and machine learning infrastructure layer through Cortex AI — a suite of capabilities that allows enterprises to build, deploy, and serve LLM-powered applications directly on their Snowflake data without moving data to external AI platforms. Cortex AI includes LLM fine-tuning, vector search, and inference APIs that integrate with leading foundation models, enabling enterprises to build RAG applications and AI agents on top of their governed Snowflake data. Snowflake serves more than 10,000 enterprise customers globally, including the majority of the Fortune 500, across industries from financial services and healthcare to retail and media.\n\nSnowflake's AI and ML workloads generate over $900 million in annualized revenue, one of the fastest-growing segments of its business. The company trades on NYSE as SNOW and competes with Databricks, Google BigQuery, and Amazon Redshift. Its enterprise penetration, multi-cloud neutrality, and the Cortex AI platform position Snowflake as a foundational layer for enterprise AI deployment where data governance and security are non-negotiable.
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