The State of Open Source AI

Mozilla’s assessment of the open-model ecosystem: the gap to closed frontier models is down to about 4 points on the Artificial Analysis index, open weights now route the majority of OpenRouter tokens, Chinese models carry 46 per cent of routed tokens against 36 for the US, and inference prices have fallen roughly 50-fold in three years. One theme is that value is accruing above the model, in orchestration, tools, memory and permissions. As one HN commenter put it: “the harness is what takes these random and hallucinogenic models and makes them into something deterministic and useful”.

Pairs with harness engineering on the value-above-the-model theme, and with America’s open-model paradox on how it got this way.

The HN discussion spent as much energy on the report’s scroll-animated presentation as on its substance (“Open ships easy. Open deploys hard.”), but the sharper thread speculates that open weights eventually undercut the frontier labs’ economics entirely: hyperscalers run them without licensing fees while the labs carry the training costs.