For AI startups, choosing a model isn’t necessarily a one-time architecture decision anymore.

Open models are improving. Frontier APIs keep advancing. Models can be customized for specific workloads, and some companies are building products that use multiple models rather than committing to one. That gives founders more ways to build — and more decisions about where to spend, what to own, and how much flexibility to preserve as the technology changes.

At TechCrunch Disrupt 2026, four conversations approach those decisions from different points in the AI stack, from multi-model applications and customized models to infrastructure and the chips underneath them.

Secure your Disrupt pass to hear how AI leaders are navigating those choices. Save up to $100 on your pass now and get a second pass at 50% off. Or for a limited time, get a $75 Expo+ Pass if you’ve been affected by a layoff.

Choosing between open and proprietary models assumes a company needs to choose one in the first place. Increasingly, AI products can call on different models for different jobs.

The session “The Real Tokenmaxxing: How the Best AI Companies Navigate a Multi-Model World” will bring together Mo Jomaa, partner at CapitalG; Vipul Ved Prakash, co-founder and CEO of Together AI; and Zuzanna Stamirowska, CEO and co-founder of Pathway, on the Builder’s Stage.

They’ll explore why companies are using multiple models; how they balance cost, performance, and flexibility; and when open models can outperform proprietary alternatives.

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