Ornith-1.5-35B-A3B
· llama.cpp · 8K context · 2 × Radeon PRO W7800 in one machine · 96 GB
Ornith 1.5, a 35B mixture-of-experts with built-in MTP.
79 tok/sdecode
– tok/sprefill
8Kcontext window
Earlier checkSep 7, 2026
Follow the steps below to download and run this recipe. Omarchy Local AI lists the recipes it can launch on your hardware. The server then answers on http://localhost:8000/v1.
- 1 Download the weights
hf download ornith-ai/Ornith-1.5-35B-A3B-GGUF \ --revision 12393612fd4f730ff5aadc23e9b8f9648aa49ceb
- 2 Write the server config
cat > ornith-1.5-35b-a3b.llama.cpp.8k.2x.yml <<'EOF' { "llamacpp": { "backend": "rocm", "prefer_system": false, "rocm_args": "--flash-attn on -b 2048 -ub 512 -sm tensor -ts 0.5,0.5 --load-mode dio", "rocm_bin": "b1323" }, "rocm_channel": "nightly" } EOF - 3 Start the server
docker run --rm \ --device /dev/kfd --device /dev/dri \ -p 8000:13305 \ --ipc host \ --shm-size 16g \ -v ~/.cache/huggingface:/root/.cache/huggingface \ -v $PWD/ornith-1.5-35b-a3b.llama.cpp.8k.2x.yml:/opt/lemonade/.config/lemonade/config.json:ro \ --entrypoint /opt/lemonade/lemond \ ghcr.io/lemonade-sdk/lemonade-server:v11.9.0@sha256:7c780707cd695392a8680f557c7c1d55521383a71b1c4c5a9d9e6a226a1bee91 \ --host 0.0.0.0
✓ loadLoads and serves within an hour
✓ chatAnswers a plain question and stops on its own
– reasoningThinks separately and gets 17 × 23 right
– toolsCalls a tool with the right arguments and uses the result
– contextRecalls a code buried in a prompt that fills 85% of the window
– speedDecodes at 15 tok/s or more
Passed the older check (loads and chats); a full six-check run is pending.
- Weights
- ornith-ai/Ornith-1.5-35B-A3B-GGUF @ 12393612fd ›
- Image
- ghcr.io/lemonade-sdk/lemonade-server:v11.9.0@sha256:7c780707cd695392a8680f557c7c1d55521383a71b1c4c5a9d9e6a226a1bee91
- Launch
- llama.cpp-ornith-1.5-35b-a3b-q5-k-m-8k-v2 ›
- Recipe file
- registry/recipes/amd/radeon-pro-w7800-48gb/ornith-1.5-35b-a3b.llama.cpp.8k.2x.json ›
- Model released
- Aug 18, 2026
- Tested
- earlier acceptance