Is it safer to run open-source LLMs locally to protect sensitive corporate data from leaking?

All answers to this question.

In 2025, the gap between "closed" and "open" models closed significantly. While GPT-4 still wins on complex creative reasoning, Llama 3 is incredibly capable for summarization and extraction tasks. Running these locally via Ollama or vLLM ensures your data never leaves your firewall. However, don't underestimate the hardware costs. You’ll need high-end NVIDIA GPUs (like A100s or H100s) to get decent inference speeds for a whole team. We made the switch last year for our medical research data and the peace of mind regarding HIPAA compliance was worth the infrastructure investment.

   Answered 2025-05-15 by Kimberly Vance

Do you have the internal DevOps expertise to manage the scaling and security of your own self-hosted inference servers?

   Answered 2025-05-16 by Steven Miller

Open-source is definitely the way to go for privacy. Plus, you avoid the "model drift" issues where providers change the underlying weights without telling you.

   Answered 2025-05-18 by Douglas Schmidt

• Exactly, Douglas. Having full control over the model version is essential for reproducible results in research and development.

     Commented 2025-05-19 by Michael O'Connor