Interestingly, when opening this page, the first thought I had was not that the benchmarks should be high, but 'I really hope they did not benchmaxx'. I think a model with modest benchmark scores can have much better real world utility as opposed to the current frontiers that are RL'd into being robotic and rigid.

Looks like it can be tried at https://tinker.thinkingmachines.ai/playground

I never thought i'd see the day they released a model, rather than a blog post. The Figure 3 demo being a screencap of chrome in localhost made me feel better about myself. Jokes aside, best western open weights model- very cool.

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

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

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

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.

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

competition in this space is great, especially with open models/weights. I think the answer is not closed source models. Similar to the Unix versus Linux situation in the 1990's, open source wins out. Yesterdays story about how OpenAI has now began encrypting traffic between model and agent [0], this story brings a breath of fresh air. There is nothing "Open" about hiding the communication between model and agent, especially with software that is running within a trusted environment/network. It needs to be more transparent, not less.

[0] https://www.theregister.com/ai-and-ml/2026/07/15/openai-hide...