Open-source AI model Ornith-1.5 released with performance matching claude opus 4.8

DeepReinforce has announced the release of the Ornith-1.5 series of open-source AI models, emphasizing the integration of a 'self-improvement loop' during training. This mechanism allows the models to autonomously enhance their performance by continuously generating more challenging tasks during the learning process. The largest model in the series, Ornith-1.5-397B, is based on a mixture-of-experts (MoE) architecture with 397 billion parameters, and its performance surpasses that of Claude Opus 4.8 in certain tests. Another variant, Ornith-1.5-35B-A3B, also uses a MoE architecture with 350 billion parameters, outperforming dense models such as Muse-Glimmer-30B and Gemma-4-31B. The Ornith-1.5-9B model, a dense architecture with 9 billion parameters, demonstrates superior performance in most tests compared to the parameter-heavy Gemma-4-31B. Additionally, a quantized version named Ornith-1.5-9B-Mobile is available for mobile devices, including Android phones and the upcoming iPhone 17.