> Didn’t Sol-6.1 top Astra

No, Astra is still smarter (https://artificialanalysis.ai/models/?models=gpt-6-astra%2Cg...).

> Didn’t Sol-6.1 top Astra?

On specific coding skewed benchmarks yes.

But Astra is in a different league when it comes to doing research and investigative tasks that require exploration.

For my usecases, Astra is pareto frontier - it dominates Fable 5.1 on cost. Fable 5.1 is a phenomenal model but Astra is cheaper and uses way less tokens and steps to produce similar output.

I thought the same.

My assumption is Astra is the biggest model in terms of param size and has the most intellectual horsepower.

But Sol-6.1 is more instruction tuned to perform better on the average use cases for most users, so it benchmarks better and feels better to use.

It's widely suspected that sol 6.1 is a slightly detuned version of astra 6

> It's widely suspected that sol 6.1 is a slightly detuned version of astra 6

My feel is it's the opposite of a "detune".

Sol 6.1 is likely a distillation that's highly instruction tuned and designed to perform better on benchmarks.

Sol 6.1 is incredibly incredibly slow, 20t/s slow (vs the ~70-80 of Terra 6.1 and Luna 6). It wouldn't be so much slower if it was just a distillation, surely? There's something else going on there.

But is it slower than Astra?

> Sol 6.1 is incredibly incredibly slow, 20t/s slow

How are you getting these numbers?

I have a small token/s extension for Pi. It's regularly around ~15-20t/s for Sol 6.1.

There was some (admittedly flimsy) evidence from a microsoft model description card that it's doing multiple passes through its own weights before token generation to improve output; it might be an architecture change that's making it slow, moreso than raw size

Is it using comparable tokens per task?