ornith-ai/Ornith-1.5-122B
text-generation model by ornith-ai
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Model card & documentation
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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. This model card documents Ornith-1.5-122B, the most capable and efficient.member of the Ornith-1.5 family — a 122B MOE model designed for efficient single-GPU deployment, and edge-deployable on mobile devices via its quantized Ornith-1.5-122B-Mobile variant. Ornith-1.5-122B Qwen3.8-Flash-Next (125B) Qwen3.8 (27B dense) Nemotron 3.5 Super VL (120B)…
Read the full model card ↗ · Preview checked 2026-10-30T11:29:32.519Z
Inside the original model card — Document outline
- Ornith-1.5-122B
- Ornith 1.5 122B
- Benchmarks
- Quickstart
- Serving Ornith-1.5-122B
- For Long-Context
- Using Ornith-1.5-122B via the Chat Completions API
- Basic Usage
- Agentic Usage
- Ollama
- Atomic.chat
- llama.cpp
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Model overview
ornith-ai/Ornith-1.5-122B is a text-generation model repository published by ornith-ai on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-generation
- Library
- transformers
- Recent downloads (30 days)
- 90,697
- Cumulative likes
- 198
- Hugging Face trending score
- 61
- Reported safetensors parameters
- 125,086,497,008
- Architecture
- Qwen3_5MoeForConditionalGeneration
- License
- mit
- Access
- Not gated by Hugging Face
- Created
- 2026-10-16T07:14:27.000Z
- Last modified
- 2026-10-21T08:29:30.000Z
Compatibility and lineage
Language coverage was not reported.
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-29T06:47:43.046Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.