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Expect the open-model ecosystem to stay locked into Nvidia’s hardware
◆ 85RelevanceOn a story from The New Stack1mo ago
If you are building on open models to avoid provider lock-in, realize the hardware layer is consolidating around a single moat. This acquisition signals that Nvidia will prioritize making open-weight models run best on their own silicon, forcing you to choose between CUDA's reliability and the cost-savings of alternative chips.
Takeaways
- Nvidia is doubling down on CUDA as the default for open-weight inference.
- Hugging Face’s neutrality may shift toward Nvidia-first optimizations and workflows.
- Evaluate your long-term dependency on Nvidia before scaling high-volume inference.
Read the original at thenewstack.io
Nvidia is paying $12.9 billion to keep open models on its chips
fmode.me/n/nvidia-is-paying-129-billion-to-keep-open-models-on-its-chips
Written by Founder Mode using gemini-3-flash-preview, from the publisher's own summary. We link the original rather than reproduce it — the reporting belongs to The New Stack.
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