Ollama raises $65M Series B as open-source AI tool hits 9M users

Developer tool Ollama secures major funding round

Ollama has closed a $65 million Series B funding round led by Theory Venture, bringing the company's total raised to $88 million, founder and CEO Jeff Morgan told TechCrunch. The round follows a $15 million Series A led by Benchmark's Peter Fenton, who joined the company's board.

The open-source platform, which launched in 2023, enables developers to run open-weight AI models on their personal computers with minimal setup time. The tool has accumulated 176,000 stars and nearly 17,000 forks on GitHub, reflecting widespread adoption in the developer community.

Why it matters

Ollama's rapid growth signals a broader shift in enterprise AI strategy. As inference costs mount for companies using proprietary models, open-weight alternatives are becoming economically essential rather than optional. The company's presence in 85% of Fortune 500 organizations with only 14 employees demonstrates how infrastructure tools can scale dramatically when they solve a genuine developer pain point. This funding also highlights venture capital's increasing appetite for open-source projects that establish clear paths to revenue.

From Docker to AI infrastructure

Morgan and co-founder Michael Chiang bring direct experience from building Docker Desktop, having previously created Kitematic before its acquisition by Docker. That background in developer tools proved crucial to Ollama's design philosophy.

"Open models started coming out in 2023 but they were really hard to use," Morgan explained. The models were initially designed for researchers rather than programmers, creating significant barriers to adoption. Ollama addressed this by abstracting away hardware configuration complexity, similar to how Docker simplified cloud application deployment.

The platform now serves 8.9 million developers monthly, according to Morgan.

Cloud services complement open-source roots

Beyond its free desktop tool, Ollama operates a cloud service that hosts larger, more complex models through subscription tiers ranging from free to $100 monthly. The company tracks usage based on GPU time rather than token limits, differentiating its pricing model from competitors.

This commercial direction drew criticism roughly a year ago from some community members who viewed the cloud offering as distracting from the open-source project. Morgan frames the cloud service as an extension of Ollama's core mission, noting that state-of-the-art large models are often "too big to run on your own computer."

Benchmark's Fenton emphasized that the desktop product remains unchanged: "Nothing has changed for the core product that's free on the desktop. There's zero change to the premise that this is the place you can discover and run local models."

Business momentum accelerates

The company's business inflection point arrived around January when larger open models demonstrated capability for agentic tasks like coding. Morgan cited the emergence of tools like OpenClaw as validation that open models could handle production workloads.

Fenton argues the open versus closed model debate misses the nuance: "It's not an either/or." He contends both approaches will coexist, but companies facing high inference costs have a "vital existential project" driving them toward open-weight models for routine tasks while reserving proprietary models for specialized needs.

Morgan and Fenton declined to disclose revenue figures or the company's new valuation.

Ollama joins a growing cohort of open-source AI infrastructure projects attracting venture funding, including inference providers like Inferact (maker of vLLM) and RadixArk (maker of SGLang), according to details first reported by TechCrunch.