ornith-1.5:122b

Chirp Chirp! 🐦 We are introducing Ornith-1.5, a major step toward building foundation models through end-to-end self-improvement.

Details

Updated 12 hours ago

12 hours ago

f0df8c3e9efc · 73GB

json

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244B

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390B

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1.2kB

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13MB

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6.7MB

license

1.1kB

params

{ "num_ctx": 262144, "temperature": 0.6, "top_k": 20, "top_p": 0.95 }

61B

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{ "architectures": [ "Qwen3_5MoeForConditionalGeneration" ], "dtype": "bfloat16", "hidden_size": 307

53kB

1182 tensors

73GB

Chirp Chirp! 🐦 We are introducing Ornith-1.5, a major step toward building foundation models through end-to-end self-improvement.

Ornith-1.5 extends Ornith-1.0 by expanding the self-improvement loop from scaffold and rollout optimization to jointly optimizing task generation, scaffold construction, and solution rollouts. Rather than relying on a fixed set of human-curated tasks and manually designed harnesses, Ornith-1.5 continuously generates new training tasks, discovers effective strategies for solving them, and improves the policy through reinforcement learning. For more details on the task, harness, and rollout reward design, please refer to our blog.

Model Changelog

Release Ornith-1.5-122B (Oct 20, 2026).
Release Ornith-1.5-397B, Ornith-1.5-35B-A3B, Ornith-1.5-9B (Aug 19, 2026).

Ornith-1.5-122B

Ornith-1.5-122B delivers frontier-level capabilities with exceptional inference efficiency. With superior instruction following, stronger task decomposition, and deeper understanding of real-world workflows, it achieves state-of-the-art performance among open-source models of comparable size, while running on a single NVIDIA DGX card!

Chirp Chirp! 🐦 We are introducing Ornith-1.5, a major step toward building foundation models through end-to-end self-improvement.

Details

Readme

Model Changelog

Ornith-1.5-122B

Ornith-1.5-397B

Ornith-1.5-35B-A3B

Ornith-1.5-9B