Open source models are becoming more mainstream as enterprises, governments and startups alike rely on the promise of lower costs, more control, and more flexibility. But as increasingly capable models become more freely available, how do companies capture value? And with Chinese open models gaining ground, can American players keep up?
On this episode of TechCrunch’s Equity podcast, Rebecca Bellan caught up with Irene Solaiman, Chief Policy Officer and SVP of Strategy at Hugging Face, about what startups need to know before building on open models, from choosing the right tools and infrastructure to navigating the trade-offs shaping the future of open AI.
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Chapters:
00:00 Intro
2:25 Who’s making money when open models are free?
4:08 Licenses, revenue sharing, and the Alibaba cloud advantage
8:10 What founders should check before building on open models
10:34 Why the harness matters (and why no one can evaluate it)
13:19 Buying GPUs vs. renting inference
16:20 What happens if Chinese models become the default?
22:19 Beyond language: Nemotron, bio models, and the case for an American open frontier
24:52 The OpenCode attack and the pressure to close up
28:38 Obliterated models: defenders’ tool or attackers’ gift?
34:12 How small startups can protect themselves
35:42 Outro
