We match your task with the best AI models — based on real inputs, real outputs, and what you actually care about.

Choosing the right LLM shouldn't feel like gambling.
One of our devs spent 2+ weeks testing models manually — just to automate a simple internal JSON task.

The problem?
Benchmarks didn’t reflect his task.
They were too generic, too academic, and not useful in practice.

So we built MIOSN:
A model selection tool that works the way real teams work.

With MIOSN, you can:

Define your actual task — using your own inputs & outputs
Set what matters (accuracy, cost, speed, JSON validity...)
Test multiple LLMs in parallel
Score and compare results automatically

It’s like headhunting — but for language models.

Get a clear, structured report showing:

Top-performing models for your use case

Trade-offs between cost, speed, and quality

Where each model struggles (before you deploy it)

We've been using MIOSN internally, and it's already saved us hours of guesswork.
Now we're opening it up to others facing the same challenge.

Free trial: https://www.miosn.com
Discord lab: https://discord.gg/JhWwRADE

Would love feedback from anyone building with LLMs or tired of “just try GPT-4 and see.”