A new adoption leaderboard shows that Ollama, an open-source tool for running AI models locally on personal computers, is gaining real traction among developers and organizations worldwide, ranking ahead of several major cloud-based AI services. The Open Source AI Popularity Leaderboard, launched by Scarf on August 11, 2026, tracks how widely different AI platforms are being adopted across the open-source ecosystem by measuring the number of distinct organizations downloading related packages each day.

What Does the New Leaderboard Actually Measure?

Scarf processes billions of open-source package downloads daily and analyzed nearly 700,000 tracked packages to identify AI-related tools and map them to specific model providers and inference platforms. The leaderboard counts each organization once per provider per day, regardless of how many times they download packages, which prevents large automated deployments from skewing the rankings.

The index separates two categories: model providers, which are companies that develop and publish AI models; and inference platforms, which are the software tools, hosted services, or local runtimes that actually run those models. This distinction matters because a company might appear in both categories if it offers both models and infrastructure.

How Does Ollama Compare to Cloud Giants?

The leaderboard's initial snapshot reveals a competitive landscape where open-source tools are holding their own against established cloud providers. OpenAI leads significantly in package adoption, while Amazon occupies two of the top four positions through its Bedrock and SageMaker services. However, Ollama's sixth-place ranking is particularly notable because it places the open-source platform ahead of Microsoft Azure and several other major cloud offerings.

"Open source adoption gives us another way to understand which AI technologies developers and organizations are integrating deeply. With the OSS AI Leaderboard, we want to make that signal available to the broader community," said Avi Press, Founder and CEO of Scarf.

Avi Press, Founder and CEO of Scarf

Scarf interprets Ollama's strong showing as evidence of substantial demand for local model execution and open-source AI infrastructure. This reflects a broader shift where developers and organizations want to run AI models on their own hardware rather than relying exclusively on cloud-based services.

Why the Gap Between Technical Quality and Real-World Adoption?

The leaderboard also reveals an important disconnect in the AI ecosystem: producing excellent technology does not automatically translate into widespread adoption or market dominance. Kimi, for example, has created prominent open-weight models but ranks lower in package adoption metrics. This illustrates a familiar challenge for open-source creators: releasing strong technology requires separate effort to achieve distribution, market share, and commercial value.

The rankings measure package adoption rather than underlying model consumption, so they do not track API requests, token volume, provider revenue, or which specific models organizations run through general-purpose platforms. For instance, when someone downloads an Ollama package, the data attributes that to Ollama, but it does not reveal which AI model they subsequently used with it.

How to Use This Data for Your AI Strategy

• Evaluate Platform Support: Developers and maintainers can use the leaderboard to determine which providers and runtimes their projects need to support, based on real organizational adoption patterns rather than marketing claims.
• Monitor Market Trends: AI companies, researchers, investors, and analysts can track changes in the open-source AI landscape over time to identify emerging platforms and shifting developer preferences.
• Assess Infrastructure Decisions: Organizations considering whether to adopt local AI tools like Ollama can see that thousands of other companies are already using them, providing confidence that the ecosystem is mature enough for production use.

Scarf plans to expand the leaderboard's coverage as it identifies additional provider-associated packages and gains access to new data sources. Organizations seeking granular historical data or a live feed of adoption metrics can contact Scarf directly.

The leaderboard represents a shift in how the AI industry measures success. Rather than relying solely on benchmark scores, model releases, or product announcements, the new index provides a window into what developers and organizations are actually using in production environments. Ollama's sixth-place finish suggests that the era of local, self-hosted AI is no longer a niche preference but a mainstream choice for a significant portion of the developer community.