deepreinforce-ai/Ornith-1

项目解读

Aloha! 🌺 Ornith-1.0 is a self-improving open-source models for agentic coding. README 重点章节包括：Ornith-1.0、Benchmarks、Ornith-1.0-9B、Ornith-1.0-35B。

README / GitHub 亮点

• Aloha! 🌺 Ornith-1.0 is a self-improving open-source models for agentic coding.
• Licence: MIT licensed, globally accessible, and free from regional limitations.
• Each model is evaluated against its size-appropriate baselines. All three use the same harnesses and decoding setup (see the notes under the tables).
• Terminal-Bench 2.1 (Terminus-2) 43.1 21.3 41.4 21 42.1。

适用场景

适合评估 AI 应用、智能体工作流、模型工具链、RAG/提示词工程或 AI 辅助开发场景。

采用前核查

采用前仍需核查许可证、维护节奏、issue 质量、release 记录和生产适配成本。

README 摘要

Aloha! 🌺 Ornith-1.0 is a self-improving open-source models for agentic coding. State-of-the-Art Coding Agents: Available in 9B-Dense, 31B-Dense, 35B-MoE, and 397B-MoE (post-trained on top of Gemma 4 and Qwen 3.5), achieving state-of-the-art performance among open-source models of comparable size on coding benchmarks such as Terminal-Bench 2.1, SWE-Bench, NL2Repo and OpenClaw. Self-Improving Training Framework: Ornith-1.0 employs RL to learn to generate not only solution rollouts, but also the scallfold that drive…