Ollama Raises $65M as Users Near 9M

The Docker guys did it again

If you have ever tried to run an open AI model on your own laptop, you may know the pain: cryptic setup steps, hardware quirks, and documentation written for researchers rather than working programmers. Ollama exists to make that pain go away. Type a command, wait a few minutes, and a model is running. That simple promise has now attracted serious money.

The company just raised a $65 million Series B led by Theory Ventures, on top of an earlier $15 million Series A led by Benchmark's Peter Fenton. That brings total funding to $88 million, not bad for a team of only 14 people.

What Ollama actually does

Ollama, which launched in 2023, helps developers run open-weight AI models directly on their own machines. Open-weight means the model's trained parameters are published, so anyone can download and run them, unlike closed models where you only get access through an API. Ollama also lets you browse and find models, and reach bigger, heavier ones it hosts on its own cloud through subscription tiers from free to $100 a month. Usage there is tracked by GPU time rather than token limits.

The founders, Jeff Morgan and Michael Chiang, previously helped build Docker Desktop, the tool that made shipping cloud apps easier by hiding the hardware headaches. Ollama is essentially the same trick applied to AI. As Morgan puts it, open models arrived in 2023 but were "really hard to use" because they were built for researchers, not builders.

Why it matters now

The numbers are striking. Morgan says Ollama is used by more than 8.9 million developers every month and sits inside 85% of the Fortune 500. On GitHub it has racked up 176,000 stars and nearly 17,000 forks, the platform's rough measures of popularity and how often people copy a project to tinker with it.

Morgan points to a turning point around January, when larger open models became capable of "agentic" tasks like coding, meaning they can carry out multi-step work rather than just answering questions. That shift feeds a growing industry bet: cost-conscious enterprises and startups will lean on cheaper open models for daily work and save pricier closed models for when they really need them.

Fenton, who joined the board, thinks the open-versus-closed debate is framed wrong. "It's not an either/or," he says. But he argues that any company facing high inference costs, the expense of actually running models, has a strong pull toward open-weight options. That trend, conveniently, is good news for Ollama's paid cloud service.

The grumbling in the background

Not everyone is thrilled. About a year ago, some blog and social media posts complained that Ollama's cloud business was pulling focus from the beloved free tool, citing it as an example of the "enshittification" of developer tools, the term for products that get worse as they chase revenue.

Morgan frames the cloud service differently. The best open models are often too big to run on a personal computer, so the company decided to help users find the compute for them. Fenton is blunter: "Nothing has changed for the core product that's free on the desktop."

Worth noting: both Morgan and Fenton declined to share revenue figures or the new valuation, so the business case here rests on user counts and their own read of the market.

What's next

Ollama is part of a wider pattern. AI is spawning a fresh crop of open source projects that turn into venture-backed companies, from inference providers to teams building open models from scratch. Whether Ollama can keep its free fans happy while growing a paid business is the tension to watch. If it manages both, it will have pulled off the Docker playbook a second time. If not, the enshittification critics will feel vindicated.