John Lynch

[Robert Pisarczyk @R_Pisarczyk]

An LLM answered “CNN” when asked which company Larry King worked for. The benchmark gave it zero points. The reference answer? “CNN’s”.

We found similar issues across extraction benchmarks. Good datasets, misleading scores.

https://t.co/XO2fWDCH4p

[John Lynch @J_PLynch]

Huge day at Blatent! It's been a huge shift from the team to get here.

Go on and give it a try. I think we've big things ahead! 🚀

[Robert Pisarczyk @R_Pisarczyk]

Very excited to finally share what we've been building!

Today, we are launching Blatent Struct, our first language model. 🚀

One thing that's always bothered us about building with LLMs is how much engineering you need around the model. Getting an answer is one thing. Making sure it follows the right decision path, returns everything your application needs and doesn't break your business rules is another.

We wanted to change that.

Struct brings programmability to language models.

You can define complex, cascading decisions, conditional dependencies and exactly what each outcome must satisfy. You can also enforce business rules and permissions during inference.

And rather than stitching together multiple model calls, Struct can handle the whole decision tree in a single run.

We also spent a lot of time making sure this doesn't come at the expense of performance.

In our benchmarks, Struct achieves comparable accuracy to Claude Sonnet 5.5, at 11× the speed and over 100× lower estimated cost.

It's also over 2× faster than Jev, with higher average accuracy across 20 benchmarks. And on source-grounded extraction, it outperforms Cloudflare Clairic (87.5% vs. 81.7% across six benchmarks), at 62% lower estimated cost.

For me, the exciting part is what this enables: everything from document processing and customer support to agents that can make complex decisions while respecting the rules you've set.

This is just our first model, and there's a lot more to come.

I'd love for you to give it a try and tell us what you think. We're especially keen to hear what works, what doesn't and what you'd like us to build next.

🚀 Get started for free (up to 100m input tokens are on us) : https://t.co/iwEo6Cybo2

[John Lynch @J_PLynch]

@Nezler tweeter