Today, we are introducing Ornith-1.5, a major step toward building foundation models through end-to-end self-improvement. Ornith-1.5 extends the self-scaffolding framework introduced in Ornith-1.0 into a more complete self-improvement loop: the model proposes new tasks, generates task-specific scaffolds, and produces solution rollouts for reinforcement learning, continuously creating new learning experiences from which it can improve. Ornith-1.5 spans three model scales: 397B MoE, 35B MoE, and 9B Dense. It extends Ornith-1.0, which was developed on top of Qwen3.5 and Gemma 4 with additional co