Audience
AI coding-agent researchers and developer-tool teams that need open models for scaffolding, terminal tasks, repository repair, and agentic software engineering
About Ornith-1.0
Ornith-1.0 is a self-improving family of models built specially for agentic coding tasks. It 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, Ornith-1.0 achieves state-of-the-art performance among open-source models of comparable size on coding benchmarks. Its key innovation is a self-improving training framework that learns to generate both solution rollouts and the task-specific scaffolds that guide those rollouts. Instead of relying on fixed, human-designed harnesses, Ornith-1.0 treats the scaffold as a learnable object that co-evolves with the policy, allowing the model to jointly optimize the orchestration and the final solution.
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Pricing
Starting Price:
Free
Free Version:
Free Version available.
Integrations
No integrations listed.
Company Information
DeepReinforce
United States
deep-reinforce.com/ornith_1_0.html
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