Ornith-1.0 launched: open-source AI models from 9B to 397B parameters use self-improving framework to achieve state-of-the-art coding performance, matching Claude Opus 4.7 on benchmarks.

Ornith-1.0: Self-Scaffolding LLMs for Agentic Coding

Aloha! 🌺 Today, we are introducing Ornith-1.0, a self-improving family of open-source models specially for agentic coding tasks. Ornith-1.0 spans the full spectrum, from compact 9B Dense models suitable for edge device deployment to 397B MoE frontier-scale models optimized for maximum performance, with variants including 9B Dense, 31B Dense, 35B MoE, and 397B MoE. Built on top of pretrained Gemma 4 and Qwen 3.5, it achieves state-of-the-art performance among open-source models of comparable siz...