pen source models may be struggling to keep up with their closed-off counterparts.

According to data released Thursday by the research institute Epoch AI, open weight models tend to lag around 3 months behind closed source models in capability. 

Using the institute’s Epoch Capabilities Index, which measures model capabilities across companies like Google, OpenAI, Anthropic, Meta and xAI, open-weight models score an average of seven points lower than closed source ones. Epoch notes that this is roughly the capability gap between OpenAI’s o3, released in mid-April of this year, and GPT-5, released in early August.

Open source AI offers several benefits, such as increased accessibility to AI and open collaboration for faster innovation. But open source tech projects generally struggle to stay financially solvent, one analyst previously told The Deep View.

Though open source AI has seen some wins in recent months, such as Reflection AI’s $2 billion funding round in October and DeepSeek’s explosive debut at the beginning of this year, privately developed models are receiving far more attention. In this privatization, AI research and development may be slowly slipping out of academia’s hands. 

An article published Thursday by researchers from Stanford University’s Human-Centered AI institute, including Fei-Fei Li and Christopher Manning, claims that “The tide of openness in AI is receding.” As AI labs turn inward, carrying on the mantle of “open science” and AI for “public good” has fallen to universities. 

“When AI knowledge becomes privatized, we lose more than transparency: we lose the cross-pollination of ideas that drives genuine scientific progress,” the researchers note. “Universities and public institutions are uniquely positioned to sustain this public-good role because they are not structured primarily around shareholder return or product rollout.”