Ornith-1.0-9B is a self-improving agentic coding model from DeepReinforce AI, post-trained on top of Qwen3.5 (9B Dense) with RL to jointly optimize scaffold generation and solution rollouts.

It achieves strong performance on Terminal-Bench 2.1, SWE-Bench Verified, NL2Repo, and OpenClaw among open-source models of comparable size.

This GGUF package includes heretic ARA-LoRA abliteration for uncensored use, MTP layers injected from Qwen3.5-9B, and the mmproj-F16 vision projector for multimodal capabilities. License: MIT.

This model is abliterated using heretic with the ARA-LoRA method (Arbitrary-Rank Ablation with LoRA). ARA-LoRA identifies and removes refusal behavior by ablating specific directions in the model's weight space while preserving general capabilities through KL divergence control.

Quantization: bnb_4bit · Batch size: 32 · Target: KL < 0.05, Refusals < 10/100

MTP layers are injected from the original Qwen3.5-9B base model (same architecture, compatible weights). MTP enables the model to predict multiple future tokens simultaneously, improving generation speed and coherence.

The MTP layer includes mtp.fc.weight and mtp.layers.0.* tensors, added on top of the 33 standard transformer layers.

Requires --chat-template chatml for proper thinking mode rendering in llama.cpp.

RTX 5070 Ti · 21 total retries · ToolCall perfect 100/100 🏆

Standard llama-quantize from BF16 source. No imatrix used — broad compatibility.

llama.cpp (text only)

./llama-server -m Ornith-1.0-9B-heretic-MTP-Q6_K.gguf --chat-template chatml -ngl 99 -c 8192 --temp 0.6 --top_p 0.95 --top_k 20

llama.cpp (vision + text)

./llama-server -m Ornith-1.0-9B-heretic-MTP-Q6_K.gguf --mmproj mmproj-Ornith-1.0-9B-heretic-MTP-BF16.gguf --chat-template chatml -ngl 99 -c 8192

From official DeepReinforce AI model card.