Ornith-1.5-35B-A3B

EXL3 4 bpw · tabbyapi · 128K context · RTX 3090 · 24 GB

Ornith 1.5, a 35B mixture-of-experts with built-in MTP.

– tok/sdecode

– tok/sprefill

128Kcontext window

Earlier checkearlier

Run it

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 ultimatechris/Ornith-1.5-35B-A3B-EXL3-4bpw \
  --revision 875ac67dae8e793770396908c575c507f4cd5f75 \
  --local-dir ~/models/Ornith-1.5-35B-A3B-EXL3-4bpw-875ac67d

2 Write the server config

cat > ornith-1.5-35b-a3b.tabbyapi.128k.yml <<'EOF'
network:
  host: 127.0.0.1
  port: 5000
  disable_auth: true
  disable_fetch_requests: true
  send_tracebacks: false
  api_servers: ["OAI"]
  sse_ping_interval: 15

logging:
  log_prompt: false
  log_generation_params: false
  log_requests: false
  log_chat_completion_requests: false

model:
  model_dir: /workspace/models
  inline_model_loading: false
  use_dummy_models: false
  model_name: Ornith-1.5-35B-A3B-EXL3-4bpw
  backend: exllamav3
  max_seq_len: 131073
  cache_size: 532480
  cache_mode: Q6
  tensor_parallel: false
  gpu_split_auto: true
  autosplit_reserve: [192]
  chunk_size: 2048
  output_chunking: true
  max_batch_size: 4

draft_model:
  draft_mode: disabled

sampling:
  override_preset:

memory:
  sysmem_recurrent_cache: 4096
  sysmem_kv_cache: 0
  cuda_malloc_async: true
EOF

3 Start the server

docker run --rm \
  --gpus all \
  -p 8000:5000 \
  --network host \
  --shm-size 8g \
  -e NVIDIA_VISIBLE_DEVICES=all \
  -v ~/models/Ornith-1.5-35B-A3B-EXL3-4bpw-875ac67d:/workspace/models:ro \
  -v $PWD/ornith-1.5-35b-a3b.tabbyapi.128k.yml:/app/config.yml:ro \
  --entrypoint /opt/venv/bin/python3 \
  ghcr.io/theroyallab/tabbyapi:cu13@sha256:ffa8388f310d3c8a2727c66d14a76bb663fdb99a2a49e68a43c3bebb5a3e53f1 \
  main.py \
  --config /app/config.yml

What it passed

✓ 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.

Details

Weights: ultimatechris/Ornith-1.5-35B-A3B-EXL3-4bpw @ 875ac67dae ›
Image: ghcr.io/theroyallab/tabbyapi:cu13@sha256:ffa8388f310d3c8a2727c66d14a76bb663fdb99a2a49e68a43c3bebb5a3e53f1
Launch: tabbyapi-ornith-1.5-35b-a3b-4-bpw-128k ›
Recipe file: registry/recipes/nvidia/rtx-3090-24gb/ornith-1.5-35b-a3b.tabbyapi.128k.json ›
Model released: Aug 18, 2026
Tested: earlier acceptance