Ornith 1.0 35B — MXFP4 MoE GGUF
MXFP4 MoE quantization of deepreinforce-ai/Ornith-1.0-35B, a 35B parameter Qwen3.5 MoE coding agent with 256 experts (8 active per token).
About the Model
Ornith-1.0-35B is the lightweight member of the Ornith family, designed for efficient single-GPU deployment.
- State-of-the-Art Coding Agents: Post-trained on top of Qwen 3.5, achieving state-of-the-art performance among open-source models
- Self-Improving Training Framework: Ornith-1.0 employs RL to learn to generate not only solution rollouts, but also the scaffold that drives those rollouts
- 35B total parameters with 8B active per token (256 experts, 8 active)
- 40-layer MoE architecture with sliding + full attention hybrid
- 262K context window
- MIT License — globally accessible, no regional limitations
Architecture
- Text model: Qwen3.5 MoE — 40 layers, 2048 hidden, 256 experts (8 active/token)
- Vocabulary: 248,320 tokens
Quantization
Quantized from the BF16 safetensors using llama.cpp (build 537).
MXFP4 MoE uses microscaling FP4 for expert weights and Q8_0 for non-expert tensors, optimized for MoE architectures.
Files
| File | Size | Description |
|---|---|---|
ornith-1.0-35b-mxfp4_moe.gguf | ~18.4 GB | MXFP4 MoE quantized model |
Usage
llama-server \
-m ornith-1.0-35b-mxfp4_moe.gguf \
-ngl 99 \
--host 0.0.0.0 \
--port 8080
Hardware Requirements
- Minimum: 20 GB VRAM
- Recommended: 24+ GB VRAM for full GPU offload
License
MIT