Open-weight AI models are getting cheaper and better. Here's how to use them without taking on the cost of running them

VentureBeat · Sean Falconer, Confluent · 2026-10-31 19:00 UTC

In computing, whenever a cheaper, more open alternative shows up, it’s often framed as a winner-takes-all fight to the finish. We saw it with Linux and Windows, and again with Android and iOS. In reality, both sides “won” those battles because they serve different markets, and seeing it as “either-or” was never the...

In computing, whenever a cheaper, more open alternative shows up, it’s often framed as a winner-takes-all fight to the finish. We saw it with Linux and Windows, and again with Android and iOS. In reality, both sides “won” those battles because they serve different markets, and seeing it as “either-or” was never the right lens to begin with.

A similar pattern is playing out with AI models. While proprietary models from OpenAI and Anthropic dominate enterprise use, inference token spend has been gradually shifting to open weight models. Andreessen Horowitz has reported that 37% of enterprises were running five or more models in production, including open and closed.

The real risk to a business isn't picking the wrong side, it’s getting so locked into a single model provider that switching later becomes too costly or impractical.

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