Folks are concerned that nvidia won't support these efforts if it gets models running on competing hardware. Two responses:
- The projects started without HF/nvidia involvement and were massively successful BECAUSE folks want to run models on their own devices.
- With highly capable agents, "hard to implement" should be less of a barrier. The inference market should in some sense become more efficient, as agents should make it easier to transition between software and hardware solutions. Sure there might be less training data for integration platforms, but if we've learned anything in the past few weeks, it's that agents can be remarkably persistent.
Welp, that's it then. Soon HuggingFace will require an NVidia Developer account, an onerous license agreement that must be agreed to during registration and a bloated cli interface with loads of telemetry.
Why are we not seeing xcancel alternative links?
X threw a fit.
Translation: Gervanov's ggml.ai was acquired by Huggingface in Feb 2026, so he is now "excited about the journey" after the Huggingface acquisition by Nvidia.
Can we take this as an official statement that Nvidia supports local models?
Why would Nvidia increase GPU efficiency for local models? Surely they'll operate like athletes and only establish a new record from time to time when necessary.
A company that calls Israel it's "second home" bought HuggingFace. I know how this story is going to end. I regret relying on HuggingFace and llama.cpp because of this acquisition. I'm actively exploring other options before this becomes part of another geopolitical arms race.
I follow llama.cpp pretty closely as I use either llama.cpp itself or projects that depend on it all the time, and one thing that I don't think gets talked about is the sheer scale of community involvement. It seems like a logistical nightmare, but somehow thousands of different contributors are opening hundreds of PR's every week and getting them merged in to support various hardware or implement a new pattern or algorithm from a recent research paper. It's really quite awe inspiring for me to see, and think it is in no small part because of the leadership of ggerganov - so I'm happy to see that he is sticking around and plans to keep building this incredibly useful tool that has grown into a huge community at this point.