Ornith-1.0-35B is a self-improving agentic coding model from DeepReinforce AI, post-trained on top of Qwen3.5 with RL to jointly optimize scaffold generation and solution rollouts.

It achieves state-of-the-art performance among open-source models of comparable size on Terminal-Bench 2.1, SWE-Bench Verified/Pro/Multilingual, NL2Repo, and OpenClaw.

This GGUF package includes the mmproj-F16.gguf vision projector for multimodal (image + text) capabilities with llama.cpp. MTP layers are sourced from Qwen3.5-35B-A3B (same architecture, compatible weights). License: MIT.

RTX 5070 Ti · No-thinking mode achieves better practical reliability (fewer retries).

llama.cpp (text only)

hf download SC117/Ornith-1.0-35B-MTP-APEX-GGUF --include "*.gguf" --local-dir ./models ./llama-server -m ./models/Ornith-1.0-35B-MTP-APEX-I-Compact.gguf -ngl 99 -c 131072

llama.cpp (vision + text)

./llama-server -m ./models/Ornith-1.0-35B-MTP-APEX-I-Compact.gguf --mmproj ./models/mmproj-F16.gguf -ngl 99 -c 131072

These GGUF files are quantized using APEX, an MoE-aware mixed-precision quantization technique. APEX classifies every tensor by its role — routed expert, shared expert, or attention — and applies a layer-wise precision gradient, giving sensitive edge layers higher precision and compressing redundant middle layers more aggressively.

APEX beats Q8_0 perplexity at half the size — and even beats F16.