8.9 Million AI Users

2026-07-09 · Source: Tomasz Tunguz · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering, Emerging Technologies & Innovation · Depth: Fundamental Awareness, quick

Summary

Ollama, an AI platform, is utilized by over 8.9 million developers, with its user base expanding by nearly one million weekly. This platform simplifies AI deployment, enabling users to run open-source models locally on laptops in seconds, supporting applications like Claude Code, Codex, and Hermes. For more complex tasks, Ollama offers a cloud service noted as twice as fast as competitors. The platform sees significant enterprise adoption, with 85% of Fortune 500 companies using it across sectors such as healthcare, finance, and energy, benefiting from local data processing that ensures data privacy and model ownership. Ollama partners with major open-source model providers, including Google, Meta, and NVIDIA, offering thousands of models like GLM-5.2, Kimi K2.7, Gemma, Qwen, and Ornith. The company recently secured a \$65 million Series B investment, led by the author's firm, with participation from Benchmark and YC.

Key takeaway

For Software Engineers evaluating AI deployment solutions, Ollama presents a compelling option for running open-source models locally, ensuring data privacy and customization. Its rapid adoption by over 8.9 million developers and 85% of Fortune 500 companies underscores its effectiveness and scalability. You should consider integrating Ollama for your local AI workloads and exploring its cloud capabilities for complex tasks, especially if data sovereignty is a priority.

Key insights

Ollama facilitates widespread local and cloud deployment of open-source AI models for millions of users.

Principles

• Open models are the future of AI.
• Local execution ensures data privacy.
• Simplicity drives developer adoption.

Method

Download the Ollama app to run AI models locally on a laptop in seconds, then burst to the Ollama cloud for complex tasks.

In practice

• Run open-source models locally for privacy.
• Customize AI for specific business needs.
• Integrate thousands of models from partners.

Topics

• Ollama
• Open-source AI Models
• Local AI Deployment
• Enterprise AI Adoption
• Venture Capital
• Developer Tools

Best for: CTO, VP of Engineering/Data, AI Architect, Investor, Director of AI/ML, Software Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by Tomasz Tunguz.