Ornith-1.5-35B-A3B-Abliterated (Q3_K_M)

Ollama packaging of the Dynamic Q3_K_M GGUF from alztrk/Ornith-1.5-35B-A3B-Abliterated.

Please credit and see the original model card there. GGUF files live in alztrk/Ornith-1.5-35B-A3B-Abliterated-GGUF. The base model is ornith-ai/Ornith-1.5-35B-A3B.

This listing adds the official Ornith vision projector (mmproj-Ornith-1.5-35B-BF16.gguf) so Ollama exposes vision as well as thinking and tools.

ollama run codecraftersllc/ornith-1.5-35b-a3b-abliterated

Overview

Ornith-1.5-35B-A3B-Abliterated is a refusal-ablated variant and GGUF quantization suite of ornith-ai/Ornith-1.5-35B-A3B.

It is created through directional ablation surgery on hidden state activations across all 40 layers, orthogonally projecting refusal directions out from attention and MLP down-projection matrices.

The Hugging Face repository provides both the full-precision Safetensors checkpoint and the Dynamic GGUF quantization suite.

Ornith-1.5-35B-A3B is a reasoning model: by default the assistant turn opens with a <think> … </think> block before the final answer. It is also a vision-language MoE (text + image).

Model architecture

• Total parameters: 35.8B
• Active parameters per token: ~3.1B (8 active experts + shared experts)
• Total experts: 256
• Layers: 40 hybrid layers (DeltaNet linear attention + full attention)
• Context length: native 262,144 tokens (262K)
• This Ollama tag: Dynamic Q3_K_M (~16 GB) + CLIP vision projector (~0.9 GB)

GGUF quantizations use Dynamic Hybrid K-Quantization: core attention matrices (attn.wv, attn.wo) retain higher precision while MoE routing FFNs are quantized.

Recommended sampling

From the original Ornith / alztrk cards:

• General chat: temperature=0.6, top_p=0.95, top_k=20
• To match reported benchmarks: temperature=1.0

This Ollama model defaults to num_ctx=32768. Override at runtime if you need more of the native 262K window (KV cache grows quickly).

Disable thinking when you want a direct answer:

ollama run codecraftersllc/ornith-1.5-35b-a3b-abliterated --think=false

License and attribution

• Abliterated weights and Dynamic GGUFs: alztrk (Apache 2.0)
• Base model: ornith-ai/Ornith-1.5-35B-A3B (MIT / Apache 2.0)
• Vision projector: ornith-ai/Ornith-1.5-35B-A3B-GGUF mmproj-Ornith-1.5-35B-BF16.gguf

The user assumes full responsibility for any generated output.

If you use Ornith in research, please cite:

@misc{ornith_1_5,
    title = {{Ornith-1.5}: From Self-Scaffolding to Self-Improvement},
    url = {https://ornith.ai/ornith_1_5.html},
    author = {{Ornith Team}},
    year = {2026}
}