Sybil AI
‹ Arc Pro B70

Gemma 4 12B

· llama.cpp · 256K context · Arc Pro B70 · 32 GB

Google's Gemma 4 12B from May 2026: a compact multimodal model with thinking, good with images and documents.

48 tok/sdecode
910 tok/sprefill
256Kcontext window
Tested on this cardOct 16, 2026
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. 1 Download the weights
    hf download google/gemma-4-12B-it-qat-q4_0-gguf gemma-4-12b-it-qat-q4_0.gguf \
      --revision 29d097773436b69ff9feafd636ab4cf873786537 \
      --local-dir ~/models/gemma-4-12B-it-qat-q4_0-gguf-29d09777
  2. 2 Start the server
    docker run --rm \
      --device /dev/dri \
      -p 8000:8080 \
      --shm-size 8g \
      -e ONEAPI_DEVICE_SELECTOR=level_zero:0 \
      -e UR_L0_ENABLE_RELAXED_ALLOCATION_LIMITS=1 \
      -v ~/models/gemma-4-12B-it-qat-q4_0-gguf-29d09777:/models:ro \
      ghcr.io/ggml-org/llama.cpp@sha256:86b37d266ce85b485127adea68c9dc6d04d0ec9a64b0979844d5bbd8d66c53c5 \
      -m /models/gemma-4-12b-it-qat-q4_0.gguf \
      --alias gemma-4-12B-it-qat-q4_0-gguf \
      --host 0.0.0.0 \
      --port 8080 \
      --ctx-size 262144 \
      --n-gpu-layers 999 \
      --parallel 1 \
      --flash-attn on \
      --batch-size 2048 \
      --ubatch-size 2048 \
      --jinja \
      --reasoning-format deepseek \
      --no-mmproj \
      --metrics
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 Intel Arc Pro B70 32 GB (owner: omarchy box, EPYC 7443P, card 0000:48:00.0) on Oct 16, 2026.

Details
Weights
google/gemma-4-12B-it-qat-q4_0-gguf @ 29d0977734 ›
Image
ghcr.io/ggml-org/llama.cpp@sha256:86b37d266ce85b485127adea68c9dc6d04d0ec9a64b0979844d5bbd8d66c53c5
Launch
llama.cpp-sycl-gemma-4-12b-qat-q4-0-256k-arc-pro-b70 ›
Recipe file
registry/recipes/intel/intel-arc-pro-b70-32gb/gemma-4-12b.llama.cpp.256k.json ›
Model released
May 23, 2026
Tested
owner, Intel Arc Pro B70 32 GB (owner: omarchy box, EPYC 7443P, card 0000:48:00.0)