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First reported by bsky
DeepReinforce AI Releases Ornith-1.0: Open-Source Agentic Coding Models Up to 397B Parameters

Ornith-1.0: Open-source self-scaffolding LLM family for agentic coding, from 9B to 397B parameters

By

@ornith_

8d ago· 8 min readenNews

Summary

Ornith-1.0 is a new family of open-source AI models designed specifically for agentic coding tasks. Developed by a team (likely at Aloha), the models range from a compact 9B Dense variant for edge devices to a massive 397B MoE frontier-scale model for maximum performance. Built on top of pretrained Gemma 4 and Qwen 3.5, the models achieve state-of-the-art performance among open-source models of comparable size on coding benchmarks. The key innovation is a "self-scaffolding" approach that allows the models to improve their own coding capabilities through iterative refinement.

Source

Hacker NewsOrnith-1.0: Open-source self-scaffolding LLM family for agentic coding, from 9B to 397B parametersdeep-reinforce.com

Key quotes

· 3 pulled
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.
Built on top of pretrained Gemma 4 and Qwen 3.5, it achieves state-of-the-art performance among open-source models of comparable size on coding benchmarks.
Snippet from the RSS feed
Introducing Ornith-1.0, a self-improving family of open-source models specially for agentic coding tasks.

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