Self-hosting AI: who it's for, why, at what price
Sending your data to OpenAI or Anthropic isn't always an option. When local AI becomes the right call — and when it's just more expensive for nothing.
The question nobody asks before signing
When you use ChatGPT, Claude or Gemini through their API, your data leaves for servers that aren't yours. For a blog post, no problem. For your patients' medical records, your clients' contracts or your industrial plans, the question deserves to be asked before, not after.
And it increasingly is: according to Kong's 2025 enterprise AI report, 44% of organizations name data privacy and security as the top barrier to AI adoption. Hosting AI yourself is the answer to that barrier. But it isn't free, and it isn't for everyone.
What "self-hosting AI" means
Instead of calling a US giant's API, you run an open-weight model — Meta's Llama, Mistral, Qwen, DeepSeek — on your own infrastructure: a server in-house, or a private cloud you control. The data never leaves your perimeter.
Good news: these models have caught up. Qwen 2.5-72B reaches roughly 95% of GPT-4's level on most benchmarks. Two years ago, open-weight was a fallback. Today, for many tasks, it's a real choice.