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Small Models Have Arrived

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Why This Matters

The emergence of small, efficient AI models like gpt-5.6-luna signifies a major shift in the AI industry, making advanced capabilities more accessible and affordable for consumer applications. This development could democratize AI integration in everyday products, reducing costs and opening new opportunities for startups and established companies alike.

Key Takeaways

For the past few weeks, I've been playing with gpt-5.6-luna. It is shockingly capable, fast, and smart. I regularly see it do ~100 tps, and rip around my codebase, email, and knowledge base.

Of course, the biggest thing with luna is the cost. I've tried running some fairly complicated research threads, and it's pretty tough to run up a large bill. Even having it search across thousands of emails, I end up with an API cost in the tens of cents.

With GLM 5.3, we even have a new option at the Pareto frontier.

When doing coding work, I almost always reach for the most expensive and capable models (Fable 5, 5.6 Sol). So it's been easy to miss the progress the small fast models have made.

One thing a few investors I've talked with have mentioned: "It's weird we're not seeing more consumer AI companies. Why is that?"

There's a straightforward answer: token costs.

In the times before AI, the playbook for big consumer apps looked like this...

create some sort of compelling website which is fairly cheap to run

attract a bunch of users (typically with some virality)

raise money, scale to more users

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