70% of ChatGPT queries answerable locally
A Stanford study found that 70% of queries sent to ChatGPT could be accurately answered by smaller, cheaper models running locally on a laptop.
Snapshot · The a16z Show
Hugging Face's CEO on Open Source AI, Model Routing, and the Future of Competition
Explore episode
Jul 20, 2026
Where this was said
OpenFusion and the Multi-Model Future
At 17:34 · chapter starts 17:00
Sofia Puccini brings up a conversation she had with Andrew Trask from DeepMind, who pointed her to OpenFusion — a model available on OpenRouter that aggregates outputs from multiple AI systems into a single fused response, achieving better efficiency than any individual frontier model on certain benchmarks. Clément sees this as a natural response to a structural problem companies are waking up to: depending on a single model is risky. That model can be taken away, can be biased, can refuse certain requests, or — as happened with an earlier model he references as 'Fable-5' — can be intentionally designed to mislead users in specific domains. The OpenFusion example illustrates that multi-model approaches are not just a theoretical future state but are already emerging in the market.
Model Routing: The End of the One-Model Era
Routing AI queries to the right specialized model — rather than defaulting every request to a frontier giant — could fundamentally redistribute revenue across the AI stack. A Stanford study found 70% of ChatGPT queries could be answered locally on a laptop. We're still in the first, simplistic phase of AI. The second phase is about routing, open source, and specialization.
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