This seems like a really really great debut model for a new lab. I'm happy

too bad we'll never know how good it is, since they used a radar plot to show its benchmark scores!

the gap between 'open weights' and 'open source' is now wide enough to fit an entire corporate legal department

Interested in the implied strategy - that training a bespoke model for what you need will make economic sense over using a mass-trained model. I wonder if that's true?

The Artifical Analysis has a link on their homepage but it 404's :/

https://artificialanalysis.ai/models/inkling

My personal bet is that this model should really shine in Autoresearch NanoGPT-style speedruns because its first-class integration with Tinker

They also indicate they have a 276B A12B version, but it doesn't seem the weights are available. This might actually be able to fit in 128GB when quantized to 2 bits or so which makes it interesting.

I think we’re going to start seeing more OSS models that perform especially well on certain tasks instead of trying to be generalists like the frontier models. That’s a winning formula because if you’re building an app on a model it often has a specific set of use cases

Give me a good 180B param model that fits snuggly on an single DGX spark and I will sing your praises.

It looks like HuggingFace shows Apache-2.0 but they have AUP. How does it work together?