201–210 of 324 posts
For the most part it’s better than Nemotron, worse than GLM. This makes it the best American open weights model from what I can tell?
I'm surprised that Nemotron gets mentioned at all. In my experiments with it for coding tasks it performed extremely poorly, essentially unusable.
Do you think the barbarians are at the gates of OpenAI and Anthropic? If cheaper, open weights models can seriously take revenue away from those two labs for (frontier - 1) model use cases (which are the models most enterprises will choose) then OpenAI and Anthropic are left only with users using their latest and greatest model AND who will keep upgrading to the newer ones?
> Inkling is not the strongest overall model available today, open or closed. Instead, a combination of qualities makes it a good open-weights base for customization: multimodal capabilities, efficient thinking, and availability on Tinker for fine-tuning. Open base models that can be fine tuned on Tinker is a great business model IMO. You (i.e. an enterprise) can own your own model & have it perform frontier-or-bette…
> that can be fine tuned on Tinker Good source to understand why this is valuable?
Post-training/fine-tuning is not trivial and having it as a service might make it more accessible.
For a first model, and given it's open, I am gaining some faith in American Open research labs again... I couldn't test it since it's not on openrouter or something, but even if it's only as good as GLM5.1 that's more than good enough first attempt, I think. Perhaps a lot more labs will catch up to ballpark frontier esque level soon, I am all for more competition in any field.
NVIDIA is building Nemotron
Optimizing models to be fine-tuned is an amazing direction, but just makes me wonder how much better this actually is at being fine-tuned compared to other models. As none of the modern models are great at being fine-tuned afaik. Basically looking for some sort of benchmark showing that it's resistant to overfitting / catastrophic forgetting, etc.
Would be very interesting to see concrete demonstrations of different fine-tunes of the model. I'd imagine they've done hundreds of those internally.
Do you think the barbarians are at the gates of OpenAI and Anthropic? If cheaper, open weights models can seriously take revenue away from those two labs for (frontier - 1) model use cases (which are the models most enterprises will choose) then OpenAI and Anthropic are left only with users using their latest and greatest model AND who will keep upgrading to the newer ones?
Bull case: iteration becomes so quick that frontier-1 won't cut it. OpenAI and Anthropic are both betting on the singularity, I suppose.
Here's a pelican: https://tools.simonwillison.net/markdown-svg-renderer#url=ht...