Model Card: Ornith-1.5-122B
Ornith-1.5-122B: 122B total parameters (MoE, active parameter count undisclosed), 262,144-token native context (extendable to roughly 1M with YaRN scaling factor 4.0), MIT license, deployable on a single 80GB GPU; uploaded to HuggingFace on 2026-10-16 with no accompanying blog post, surfacing instead through community coverage and HF trending; scores 84.5% on SWE-bench Verified (non-hack) and 80.0% on CyberGym, both ahead of the similarly sized Qwen3.8-Flash-Next (125B); the training method carries over Ornith-1.0's self-improvement loop but extends it from optimizing scaffolds and rollouts alone to jointly optimizing task generation, scaffold construction, and rollouts; no official or third-party hosted API pricing exists yet.