LOCAL AIregistry
‹ RTX 4070 Ti SUPER

Qwen3.5-9B

EXL3 6 bpw · tabbyapi · 128K context · RTX 4070 Ti SUPER 16 GB

Alibaba's 9B model from February 2026: small enough for an 8 GB card, with a 64K–128K window. It thinks, calls tools and stays quick on modest hardware.

139 tok/sdecode
2,241 tok/sprefill
128Kcontext window
Tested on this cardSep 26, 2026
Run it

With Omarchy Local AI it is one button. By hand, it is three steps: the weights, the config, the container. The server then answers on http://localhost:8000/v1.

  1. 1 Download the weights
    hf download TheMelonGod/Qwen3.5-9B-exl3 \
      --revision 7fbc2095db50b0d56f7f07ac84903f98f883d3b9 \
      --local-dir ~/models/Qwen3.5-9B-exl3-7fbc2095
  2. 2 Write the server config
    cat > qwen3.5-9b.tabbyapi.128k.yml <<'EOF'
    network: {host: 0.0.0.0, 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
      model_name: Qwen3.5-9B-exl3-7fbc2095
      backend: exllamav3
      inline_model_loading: false
      max_seq_len: 131072
      cache_size: 264192
      cache_mode: Q4
      tensor_parallel: false
      gpu_split_auto: true
      autosplit_reserve: [256]
      chunk_size: 2048
      output_chunking: true
      max_batch_size: 2
      vision: false
      reasoning: true
      start_in_reasoning: auto
      tool_format: qwen3_coder
      template_vars_default: {}
    draft_model: {draft_mode: mtp}
    memory: {sysmem_recurrent_cache: 4096, sysmem_kv_cache: 0, cuda_malloc_async: true}
    EOF
  3. 3 Start the server
    docker run --rm \
      --gpus all \
      -p 8000:5000 \
      --shm-size 8g \
      -v ~/models/Qwen3.5-9B-exl3-7fbc2095:/workspace/models/Qwen3.5-9B-exl3-7fbc2095:ro \
      -v $PWD/qwen3.5-9b.tabbyapi.128k.yml:/app/config.yml:ro \
      --entrypoint /opt/venv/bin/python3 \
      ghcr.io/0xsero/tabbyapi-exl3@sha256:0f83e6198dc3be2561652d8df2525a7d1a69733e12fc8e25cbc5bc319a8a3ad1 \
      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 all six checks on a real RTX 4070S Ti on Sep 26, 2026.

Details
Weights
TheMelonGod/Qwen3.5-9B-exl3 @ 7fbc2095db ›
Image
ghcr.io/0xsero/tabbyapi-exl3@sha256:0f83e6198dc3be2561652d8df2525a7d1a69733e12fc8e25cbc5bc319a8a3ad1
Engine profile
tabbyapi-exl3 ›
Recipe file
registry/recipes/nvidia/rtx-4070-ti-super-16gb/qwen3.5-9b.tabbyapi.128k.json ›
Model released
Feb 26, 2026
Tested
vast, RTX 4070S Ti