Ornith-1.5-35B-A3B-GGUF

Ornith-1.5-35B-A3B

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 (which was developed on top of Qwen3.5 and Gemma4 with additional continued pretraining, mid-training, and post-training) 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.

Ornith 1.5 35B-A3B

This model card documents Ornith-1.5-35B-A3B, the mid-size mixture-of-experts member of the Ornith-1.5 family. It activates only ~3B parameters per token, yet significantly outperforms its similar-sized peer Qwen 3.6-35B across all coding and agentic benchmarks, and outperforms dense models such as Gemma 4-31B and Muse Glimmer-30B by wide margins on agentic coding.

Benchmarks

Ornith-1.5-35B-A3B
Ornith-1.0-35B-A3B
Qwen3.6-35B-A3B
Gemma-4-31B
Muse-Glimmer-30B
Qwen3.5-397B

Coding

Terminal-Bench 2.1 (Terminus-2)
67.8
64.2
52.5
42.1
51.7
53.5

Terminal-Bench 2.1 (Claude Code)
68.5
62.8
49.2
-
-
48.6

SWE-bench Verified
79
75.6
73.4
52
76
76.4

SWE-bench Pro
59.6
50.4
49.5
35.7
51.2
51.6