Nvidia will lead a panel at TechCrunch Disrupt 2026 on choosing between open and proprietary AI models
TechCrunch Disrupt 2026 (13–15 October, San Francisco) hosts a panel by Nvidia on choosing between open and proprietary AI models for startups. According to Nvidia, its open Nemotron models were cited by 145 papers at ICML 2026; the open model Nemotron 3 Super has 120 billion parameters.
At TechCrunch Disrupt 2026 (13–15 October, San Francisco), the Builders Stage will host a panel discussion titled “The Open vs. Closed AI Debate Is Just Getting Started”, led by representatives from Nvidia – Nader Khalil, director of developer technologies and co-founder of Brev.dev (acquired by Nvidia in July 2024), and Sydney Sykes, head of global VC partnerships at Nvidia. The discussion is expected to focus on the business trade-offs between open and proprietary AI models for startups – covering costs, control over data, infrastructure, development speed and long-term competitive advantage.
According to Nvidia, 145 papers accepted at ICML 2026 cited its open models and datasets in the Nemotron series, across fields such as robotics, autonomous vehicles and biomedical research. The company also states that its open model Nemotron 3 Super, with 120 billion parameters and designed for agentic tasks, was introduced in March, and that companies are already combining it with proprietary models, according to Nvidia, instead of choosing between the approaches. Earlier in 2026, Nvidia CEO Jensen Huang described the company position at GTC as “proprietary and open”, not “proprietary versus open”.
According to the organizers, conference registration with a discount of up to 200 dollars is available until 25 September 2026 at 23:59 Pacific time.
Why it matters
For startups and their founders, this is a reminder that the choice between an open and a proprietary model affects costs, margins, infrastructure requirements and where the actual competitive advantage of a product comes from – the sources mention that access to a model alone (whether proprietary or open) does not in itself guarantee a moat. Nvidia advocates combining both approaches here, which is particularly relevant for companies already working with its open models in the Nemotron series or considering deploying them alongside proprietary APIs.
Two audiences, two different impacts
What this means
For individuals
For developers and startup founders, this is a reminder that choosing a model (a proprietary frontier model, an open model, fine-tuning, local deployment) is a recurring decision that affects development speed and future flexibility, rather than a one-time choice at the start of a project.
For a business
The choice between an open and a proprietary model affects costs, margins, control over data, infrastructure requirements and negotiating power with investors – Nvidia advocates combining both approaches here instead of choosing one camp, which can serve as a framework for your own decisions, not as a ready-made answer.
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Event sources
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