The performance gap between frontier AI models from US tech companies and the best open-weights models from Chinese companies has closed to just 4.4 months, according to a Mozilla report. That explains why many companies are shifting to the significantly cheaper open models for routine work—and helps reveal a narrow band of workloads where frontier models are worth the cost.
Most organizations should ideally be using open models as the default for the majority of their work, according to the latest State of Open Source AI report from Mozilla, published on September 15 and shared with Ars prior to publication. The report highlights how a leading open model, Moonshot AI’s Kimi K3, achieves a composite AI performance score on the Artificial Analysis Intelligence Index that is just three points behind Anthropic’s Fable 5 closed frontier model, all while costing just 30 percent of the latter.
“Closed [models] earns its premium in a few places: expert professional work, high-intensity retrieval, and long context,” Raffi Krikorian, chief technology officer at Mozilla, said in an email to Ars. “We see the decision to pay for closed [models] as workload-specific rather than organization-specific.”
The open-weights AI models allow anyone to download the main model components and run the models on their own computers, but developers still typically withhold vital information, such as training data, the data pipeline, and training code. By comparison, US tech companies, like Anthropic and OpenAI, mostly offer closed frontier models that keep everything proprietary, requiring customers to pay more for access.
Organizations still pay for closed frontier models because they work out of the box and come bundled with “compliance packaging, support, and accountability,” whereas many organizations lack the staff to run open-weights models well, Krikorian explained.
