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  4. Open-Source Ornith-1.5 Drops 397B MoE Model Under MIT License
Models & research

Open-Source Ornith-1.5 Drops 397B MoE Model Under MIT License

The open-source Ornith-1.5 model family released 9B Dense, 35B MoE, and 397B MoE checkpoints trained with self-improving strategies. The top 397B MoE model claims performance comparable to Claude Opus 4.8 on coding benchmarks.

August 20, 2026· 3 min read
OKCurated by Oleksandr Kuzmenko, AI Product Engineer·Updated August 20, 2026·Sources cited on every story
AI-assisted · editor-reviewed·How we use AI
Open-Source Ornith-1.5 Drops 397B MoE Model Under MIT License

Impact: Medium

Why it matters

You can download, fine-tune, or host a top-tier open-weights MoE model for local and self-hosted AI coding workflows.

TL;DR

  • 01Ornith-1.5 provides open-weights MoE checkpoints under an unrestricted MIT license.
  • 02Utilize GGUF or MLX quantizations for local testing on workstation hardware.
  • 03Evaluate the 397B MoE model as a self-hosted alternative for coding agent pipelines.

Key facts

SWE-Bench Verified Score86.0% (self-reported)
SWE-Bench Pro Score65.1% (self-reported)
SWE-Bench Verified Score
86.0% (self-reported)
SWE-Bench Pro Score
65.1% (self-reported)
License
MIT License
Supported Formats
FP8, GGUF, MLX, NVFP4

Self-Improving Agentic Architecture

Ornith-1.5 introduces an automated self-improvement loop for training foundation models. The system generates task proposals, creates custom execution scaffolds, and runs solution rollouts for reinforcement learning (RL):

  • Model Variants: 9B Dense, 35B MoE, and 397B MoE.
  • License: Permissive MIT License for unrestricted commercial and research use.
  • Quantizations: FP8, GGUF, MLX, and NVFP4 formats published on Hugging Face.

SWE-Bench Performance Metrics

The flagship 397B MoE model achieves high scores across coding and software engineering benchmarks (self-reported by vendor):

  • SWE-Bench Verified: 86.0%
  • SWE-Bench Pro: 65.1%
  • SWE-Bench Multilingual: 79.6%

Try it in 2 minutes

huggingface-cli download ornith/Ornith-1.5-397B-MoE-GGUF --include '*.gguf'

bash

✓ When to use

  • When building private on-premise AI coding tools requiring MIT license compliance.
  • When running offline agentic workflows where cloud API access is restricted.

✕ When NOT to use

  • When limited by low-RAM inference environments unable to host large MoE parameters.

What to do today

  • →Download GGUF or FP8 quantizations from Hugging Face for local testing.
  • →Benchmark Ornith-1.5 397B MoE against your internal software engineering tasks.
#Ornith-1.5#Hugging Face#Claude

Sources

  • Ornith-1.5 Announcement on X
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← Previous storyNVIDIA Releases SkillEvaluator to Benchmark AI Agent Skills in Claude Code and CursorNext story →Claude Code Feature Request Urges Adoption of Universal AGENTS.md Standard

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