A New Frontier in Focused Language Generation
After months of painstaking research, we are proud to announce Yo-GPT — the world's first purpose-built large language model that does exactly one thing, perfectly. It says "Yo."
Go ahead. Ask it anything. Philosophy, physics, your relationship problems. The answer is always the same.
Our engineers debated this for longer than it took to build.
In the real world of LLMs, "Yo" isn't just one number — it's a token (or two). A piece of vocabulary with its own ID, its own embedding, its own dreams. We gave it the spotlight it deserves.
To select "Yo" from a vocabulary of 50,000 words, we set the bias for "Yo" → ∞ and the biases for everything else to −∞. Every other word never stood a chance. Democracy was never the goal.
While a theoretical math model needs exactly 1 parameter, our production-ready Yo-GPT uses a full bias vector equal to the vocabulary size. Because over-engineering is how you get funding.
| Metric | GPT-4o | Claude Opus | Yo-GPT |
|---|---|---|---|
| Saying "Yo" Accuracy | 2.1% | 1.8% | 100% |
| Response Consistency | Variable | Variable | Perfect |
| Hallucination Rate | ~12% | ~8% | 0%* |
| Latency (p99) | 1.2s | 0.9s | 0.003s |
| Cost per Query | $0.03 | $0.04 | $0.000001 |
*It's hard to hallucinate when you only know one word. We consider this a feature.
"We trained it on every 'Yo' ever uttered. Took about four seconds. The rest of the quarter we just did stand-up."
— ANONYMOUS YO-GPT RESEARCH ENGINEER
We didn't actually build Yo-GPT. (Though honestly, the bias vector math checks out.)
But if you actually want small, task-specific models for your agents — models that do one thing really well instead of burning tokens pretending to be everything — Neurometric builds them.
Focused AI that knows what it's supposed to do. No "Yo" required.