Gemma 4 12B
EXL3 3 bpw · tabbyapi · 32K context · RTX 4060 · 8 GB
Google's Gemma 4 12B from May 2026: a compact multimodal model with thinking, good with images and documents.
31 tok/sdecode
661 tok/sprefill
32Kcontext window
Tested on this cardSep 26, 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 turboderp/gemma-4-12B-it-exl3 \ --revision 38309570753c5fde71a818feb513b1e09a81fc18 \ --local-dir ~/models/gemma-4-12B-it-exl3-38309570
- 2 Write the server config
cat > gemma-4-12b.tabbyapi.32k.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: gemma-4-12B-it-exl3-38309570 backend: exllamav3 inline_model_loading: false max_seq_len: 32768 cache_size: 33792 cache_mode: Q4 tensor_parallel: false gpu_split_auto: true autosplit_reserve: [256] chunk_size: 2048 output_chunking: true max_batch_size: 1 vision: true reasoning: true start_in_reasoning: auto tool_format: null template_vars_default: {enable_thinking: true} draft_model: {} 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 \ --shm-size 8g \ -v ~/models/gemma-4-12B-it-exl3-38309570:/workspace/models/gemma-4-12B-it-exl3-38309570:ro \ -v $PWD/gemma-4-12b.tabbyapi.32k.yml:/app/config.yml:ro \ --entrypoint /opt/venv/bin/python3 \ ghcr.io/0xsero/tabbyapi-exl3@sha256:0f83e6198dc3be2561652d8df2525a7d1a69733e12fc8e25cbc5bc319a8a3ad1 \ main.py \ --config /app/config.yml
✓ 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 4060 on Sep 26, 2026.
- Weights
- turboderp/gemma-4-12B-it-exl3 @ 3830957075 ›
- Image
- ghcr.io/0xsero/tabbyapi-exl3@sha256:0f83e6198dc3be2561652d8df2525a7d1a69733e12fc8e25cbc5bc319a8a3ad1
- Engine profile
- tabbyapi-exl3 ›
- Recipe file
- registry/recipes/nvidia/rtx-4060-8gb/gemma-4-12b.tabbyapi.32k.json ›
- Model released
- May 23, 2026
- Tested
- vast, RTX 4060