Are Small LLMs about to take over regulated industries? (If you care about privacy, you need to read this)

Are you in a regulated field like healthcare, finance, or law — and have hesitated to use LLMs or tools like GitHub Copilot in your team because of data privacy, GDPR, or regulatory pressure? If so, what I'm about to tell you might change your mind.

The Big Secret the Industry Isn't Talking About

There's a topic that, frankly, I don't see discussed enough: the incredible recent advancements in small LLMs. Instead, the industry conversation is dominated by Big Tech's narrative — Microsoft, Google, et al. — pushing their proprietary, cloud-based solutions with hefty price tags and vendor lock-in. Why? It's in their interest to keep you dependent on their infrastructure. But the real revolution might be happening elsewhere.

Small, Open-Weight Models: Quietly Getting Incredible

If you haven't been watching closely, you might have missed just how much smaller, open-weight LLMs have improved over the last year, even the last few months. In fact, these models now deliver a quality that's better than the original viral ChatGPT release from early 2023 — with the game-changing detail that they can run entirely on consumer hardware.

See for Yourself

Take a look at the image below. It shows how the new Qwen3 model (just released days ago!) scales across different hardware. Pay especially close attention to the left side: for the first time, we have models that run natively, efficiently, and usefully on a MacBook Air, a mid-range GPU, or even a compact Mac Mini — no cloud required.

Qwen3: Model Size vs Hardware

Qwen3: Why This Model is a Giant Leap

Qwen3 is the latest proof that small models can punch way above their weight. The tiny Qwen3 versions don't just parrot information — they actually demonstrate real reasoning, the kind of qualitative leap that makes AI actually useful in day-to-day, real-world workflows. For me, this is the first time LLMs that run on a MacBook Air actually "feel" smart, not just like digital Mad Libs.

And here's the kicker: the Qwen3 model is released under an Apache 2.0 license. This means:

• You can run it commercially in your organization

• You run it locally, not in the cloud—so "bringing AI to your data" really means just that

• No regulatory privacy risk; no GDPR nightmares; no IP leaving your machine or your secure data center

• No risk of your proprietary data being used to "train the next Copilot"

The End of LLM Skepticism for Regulated Domains

If you've been hesitant to experiment with AI in regulated industries—or to allow your devs, doctors, or lawyers anywhere near LLMs — those concerns are, truly, a thing of the past. You can treat these models like regular, local software: install, isolate, audit, control. Bring innovation and productivity boosts to sensitive domains without letting sensitive data escape.

The days of cloud-only, lock-in AI are numbered. Open, local, high-performing LLMs have arrived — and the best-kept secret is, they're probably already good enough for most of what you want to do.

Curious if Qwen3 or another "small but mighty" model could work for your use case? Get in touch or leave a comment below — I'd love to hear what regulated challenges you're solving!