Make frontier intelligence small enough to own.
The largest AI models are extraordinary — and largely out of reach. They live in datacenters, behind APIs, metered by the token, governed by someone else’s terms. The most important question in applied AI is no longer can a model do this? but can you run the model that does?
Distillation is the answer taking shape. It is the craft of teaching a small model to think like a large one — transferring not just answers but reasoning, judgment, and nuance from a giant teacher into a compact student you can run on a laptop, a phone, or a single GPU. It is how intelligence escapes the datacenter.
Why now
Until recently, distillation was a niche trick for compressing classifiers. Then reasoning models arrived — and with them the discovery that you can distill not just outputs but entire chains of thought. A 7-billion-parameter student trained on a frontier model’s reasoning traces can now rival systems a hundred times its size on the tasks that matter to it. The field is moving fast, and almost no one is documenting it well. We intend to.
What we’re building
The AI Distillery grows in three stages:
- A knowledgebase & blog. The clearest, most current explanation of how model distillation actually works — from first principles to the frontier. That’s what you’re reading now, and it’s where we establish that this is the place to learn the craft.
- Open tooling. As the patterns stabilize, we’ll build and open-source the things that make distilling a model approachable — recipes, pipelines, evaluation harnesses.
- A home for distilled models. A place to share, discover, and trust the small models the community distills — perhaps, one day, a marketplace.
Futuristic, but deeply human
There is something almost mythic about distillation. We take a vast, inscrutable intelligence and condense it — like a cloner drawing life from a template — into something a single person can hold and run and understand. We find that thrilling. But the point of it is profoundly human: to put capability back in the hands of individuals, to keep your data yours, to make the future of AI something you participate in rather than merely subscribe to.
That’s the bet. Come distill with us.
