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.
qrtas•4m ago
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.
spindump8930•7m ago
- 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.