Popular open source AI developer tool Ollama raises $65M, grows to nearly 9M users
TechCrunch
β’Thu, 09 Jul 2026 13:00:00 +0000
π° What Happened
Ollama, the open-source AI tool that lets developers run open-weight AI models on their PCs, raised $65 million in Series B funding led by Theory Ventures, bringing total funding to $88 million. The company has grown to nearly 9 million monthly active developers and is used by 85% of Fortune 500 companies, all with just 14 employees.
π The Backstory
Ollama was founded in 2023 by Jeff Morgan and Michael Chiang, who previously built Kitematic (acquired by Docker) and worked on Docker Desktop. Ollama solves the same problem for AI that Docker solved for cloud: abstracting away hardware complexity so developers can easily run and experiment with models locally. The tool has 176,000 GitHub stars and nearly 17,000 forks.
π― Why It Matters
Ollama's explosive growth demonstrates the massive demand for accessible, local AI development tools and signals a shift toward running AI models on-device rather than relying solely on cloud APIs. Its success also highlights the growing importance of open-source AI infrastructure alongside proprietary offerings from major tech companies.
Ollama, the open-source AI tool that lets developers run open-weight AI models on their PCs, raised $65 million in Series B funding led by Theory Ventures, bringing total funding to $88 million. The company has grown to nearly 9 million monthly active developers and is used by 85% of Fortune 500 companies, all with just 14 employees.
Ollama was founded in 2023 by Jeff Morgan and Michael Chiang, who previously built Kitematic (acquired by Docker) and worked on Docker Desktop. Ollama solves the same problem for AI that Docker solved for cloud: abstracting away hardware complexity so developers can easily run and experiment with models locally. The tool has 176,000 GitHub stars and nearly 17,000 forks.
Ollama's explosive growth demonstrates the massive demand for accessible, local AI development tools and signals a shift toward running AI models on-device rather than relying solely on cloud APIs. Its success also highlights the growing importance of open-source AI infrastructure alongside proprietary offerings from major tech companies.