Ollama raises $65 million and nears 9 million users of its AI tool
Open-source tool Ollama has raised $65 million and is close to 9 million users. The service lets developers run AI models on their own computers, without having to depend on cloud APIs. The project's popularity is reflected in nearly 176,000 stars and about 17,000 forks on GitHub, a rare scale for a local development tool.
AI-processed from TechCrunch; edited by Hamidun News
On July 9, 2026, Ollama raised $65 million in funding, and the number of users of its open-source tool for running AI locally has neared 9 million. The project lets developers run artificial intelligence models on their own computers and has already built a sizeable community on GitHub.
How the Ollama project grew
Ollama became popular by offering a simple way to run AI directly on a PC. The tool targets developers who need to deploy a model locally fast, test its capabilities, or build AI features into their own applications without necessarily calling an external cloud service.
According to the data cited in the publication, the project has collected almost 176,000 stars on GitHub. The number of forks has neared 17,000. These figures reflect not only interest in the repository but also the size of the community that uses, studies and adapts the tool.
- Funding: $65 million
- Users: almost 9 million
- GitHub stars: 176,000
- GitHub forks: almost 17,000
- Main use case: running AI on personal computers
Why developers choose local AI
Running models locally gives developers more control over their environment and data. Instead of sending every request to an external API, they can deploy a model on their own machine, which is especially handy for experiments, prototyping and building applications that need AI without a constant cloud connection.
Ollama makes this approach more accessible with a tool built specifically for developers. The project's popularity shows that demand for local AI infrastructure extends beyond enthusiasts and research teams. Almost 9 million users suggest that running models on personal devices is becoming a notable part of development practice.
That said, audience growth does not mean local execution fully replaces cloud platforms. Performance depends on the computer, the available memory and the specifics of the model. Still, for many tasks a local environment is becoming a convenient complement to cloud APIs.
What the investment will go toward
The original report does not disclose how the money will be used or the terms of the deal. All that is known is that Ollama raised $65 million amid rapid audience growth and high activity on GitHub.
The round itself matters for the market in tools around open-source AI. Investors are funding not only model developers but also products that make models easier to run and use. Ollama sits in exactly this layer of infrastructure: it connects models to programmers' everyday workflows and helps bring AI closer to the user's device.
Ollama has grown to almost 9 million users while keeping its focus on
making it simple to run AI models on developers' computers.
What this means
A $65 million round and almost 9 million users show that running AI locally is turning into a mass-market segment of its own, and that developer tools are becoming a key way to distribute open-source models.
- Nov 1, 2026MoneyGate safety layer blocked all 42 fraudulent requests to local AI models
- Nov 1, 2026ThinkJev Makes AI Think Only About Hard Questions: 28% Fewer Tokens
- Oct 31, 2026Open-source LLM gateway KTMS 1.0 plugs your own GPUs into the cloud and survives outages
- Oct 31, 202622B-Parameter LTX-2.5 Runs on a 10 GB RTX 3080, but Takes 5 Minutes per Shot
Key Questions Answered
How the Ollama project grew?
Ollama became popular by offering a simple way to run AI directly on a PC. The tool targets developers who need to deploy a model locally fast, test its capabilities, or build AI features into their own applications without necessarily calling an external cloud service. According to the data cited in the publication, the project has collected almost 176,000 stars on GitHub. The number of forks has neared 17,000. These figures reflect not only interest in the repository but also the size of the community that uses, studies and adapts the tool. Funding: $65 million Users: alm
Why developers choose local AI?
Running models locally gives developers more control over their environment and data. Instead of sending every request to an external API, they can deploy a model on their own machine, which is especially handy for experiments, prototyping and building applications that need AI without a constant cloud connection. Ollama makes this approach more accessible with a tool built specifically for developers. The project's popularity shows that demand for local AI infrastructure extends beyond enthusiasts and research teams. Almost 9 million users suggest that running models on pe
What the investment will go toward?
The original report does not disclose how the money will be used or the terms of the deal. All that is known is that Ollama raised $65 million amid rapid audience growth and high activity on GitHub. The round itself matters for the market in tools around open-source AI. Investors are funding not only model developers but also products that make models easier to run and use. Ollama sits in exactly this layer of infrastructure: it connects models to programmers' everyday workflows and helps bring AI closer to the user's device. Ollama has grown to almost 9 million users while
Test Frontier LLMs & Autonomous Agents in One Workspace
Run Claude Opus 5.5, GPT-6, Gemini 3.1, and DeepSeek side-by-side in Nomad AI (nomadnet.ai) — unified model routing, deep research, and multimodal workflows under one subscription.
The AI world, distilled — once a week
Seven stories that actually mattered, hand-picked. No noise, no reposts, no press releases.
Done! Check your inbox for a confirmation.