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Intel Arc (experimental)

Strata 0.1.39 includes an experimental Intel Arc engine: Strata's own engine ported to SYCL (Intel oneAPI). maxfridbe wrote it in #423, with fixes from the people testing it. The code is in sycl/, and the port's own notes, measurements and maintenance procedure are in docs/INTEL.md. This page covers what you need, how to build it, and what has been tested.

Experimental means: the Strata maintainers have no Intel GPU. We compile the port and run its kernel tests, but we have not run it on an Arc. Every result on Arc hardware below comes from the community. The NVIDIA and AMD engines are unchanged: the Intel build is a separate CMake target, off by default.

There is no ready-made Intel engine in the release zips. You build it from source on Linux.

What has been run, and by whom

Hardware Result Reported in
Port author Arc Pro B70 32 GB, Ubuntu 24.04 Coder IQ1_M: 70-78 tok/s decode, ~790 tok/s prompt; IQ2_XS: 51-64 tok/s; 256K context measured #423, INTEL.md
Community 2x Arc Pro B70, --layer-split Flash-Next IQ3_XXS 66 tok/s decode, 394 tok/s prompt (with the stage_room fix that is now in 0.1.39) #423
Community Arc Pro B50 16 GB Coder IQ1_M ~23 tok/s, IQ2_XS ~25-27 tok/s, up to 128K #423
Community Arc B580 12 GB, WSL2 IQ2_XS ~21 tok/s, Coder ~15 tok/s; device loss also seen #423
Community 2x Arc Pro B60 24 GB, --layer-split Coder IQ1_M: 56.6 tok/s decode, 428 tok/s prompt (2,129 tokens); Flash-Next IQ2_XS: 58.6-61.3 tok/s decode, 436 tok/s prompt; all experts in VRAM; 8K context bench/results/2026-10-04-community-2x-arc-pro-b60
Community one Arc Pro B60 24 GB Coder IQ1_M with 4,042 of 12,288 experts mirrored in RAM: 11.9 tok/s decode (needs the ring-wait fix from the same report) same
Strata maintainers no Arc compile check and kernel tests on a CPU device only (below) this release

The 0.1.39 port re-migrates 0.1.38's port onto the 0.1.39 engine sources (the #606 NaN fix, the #649 verify trace, the new prompt paths). 0.1.39's sycl/ did not compile against 0.1.39's own engine sources (#784: the ThreadAffinity type of #626 and the layer range of NativeDense::load from #559), and its ring waits never saw a slow layer as still running (#866, #867). Both are fixed in 0.1.40, and the two B60 reports below were measured with exactly those two fixes on top of 0.1.39. No one has run an unpatched 0.1.39 port on an Arc, and the other rows were measured on earlier versions.

The two B60 rows ran 6f32ec0 plus two small sycl/ fixes (the compile fix and the ring-wait fix), AOT bmg-g21, on Ubuntu 24.04 with xe, Level Zero V2, NEO 26.09.37435.12 and oneAPI 2026.1.1, without Docker. Host: Ryzen 5 5600, 64 GB RAM, PCIe 3.0 x8 per card. Full flags, per-request timings and engine logs are in the report linked in the table.

What was tested here (0.1.39)

  • Compiles: Ubuntu 24.04 (WSL2), Intel oneAPI DPC++ 2026.1.1 + oneMKL 2026.1. The whole sycl/ project builds with 0 errors: the strata engine plus all 157 targets (the kernel parity tests and benches). The build is SPIR-V (JIT). The AOT build (STRATA_SYCL_AOT) was not built here, because it needs ocloc.
  • Kernel parity tests on a CPU (ONEAPI_DEVICE_SELECTOR=opencl:cpu, Intel's OpenCL CPU runtime, AMD Ryzen 5 7600): 14 of 25 pass. That is the same set that PR #423's own 0.1.38 port passes on that device: the failures are tight float tolerances on the CPU's math (rel 3e-6 against a 1e-6 limit), model fixtures that are not present, and two tests that time out on a CPU. This is a check that the kernels compile and compute, not a test of an Arc.
  • Setup: --backend sycl warns, then hands over to sycl/setup_intel.py on Linux (unit tests: tools/test_setup_sycl.py).
  • Unchanged: the CUDA engine's greedy output, checked byte-identical against the gated 0.1.39 build (Q2_0 and Coder). The HIP build is not affected (the option is off by default).

Not tested by anyone yet: Windows (no native build path; see below), Arc on WSL2 for the 0.1.39 port, the Alchemist A-series, integrated Arc GPUs (the B390 / Panther Lake in #515; the shared-memory planning does not exist yet), and images (not wired on Intel).

What you need

  • Linux, e.g. Ubuntu 24.04, with Intel's GPU driver (the xe or i915 kernel driver plus the compute runtime / Level Zero; on Ubuntu, intel-opencl-icd libze1 libze-intel-gpu1, or Intel's client GPU guide).
  • Intel oneAPI: the DPC++ compiler (icpx, 2025.3 or newer; 2026.1 is what was built here) and oneMKL. About 5 GB.
  • cmake 3.24+, ninja, git (the build fetches ggml unless you point STRATA_GGML_DIR at a llama.cpp checkout), Python 3.
  • For setup --backend sycl today: Docker. sycl/setup_intel.py runs the engine in the strata-sycl-dev image built from sycl/tools/Dockerfile. Note that the Dockerfile starts from a community llama.cpp SYCL image (ghcr.io/snailium/...), not an Intel or Strata image.
  • VRAM: the port keeps the experts on the card (--stream-experts). A 32 GB card holds the Coder IQ1_M or IQ2_XS. Smaller cards mirror part of the experts in RAM and are slower.

Build (Linux)

Install oneAPI from Intel's apt repository (this is what was used here):

wget -qO- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB \
  | sudo gpg --dearmor -o /usr/share/keyrings/oneapi-archive-keyring.gpg
echo "deb [signed-by=/usr/share/keyrings/oneapi-archive-keyring.gpg] https://apt.repos.intel.com/oneapi all main" \
  | sudo tee /etc/apt/sources.list.d/oneAPI.list
sudo apt update
sudo apt install intel-oneapi-compiler-dpcpp-cpp intel-oneapi-mkl-devel ninja-build cmake git

Then build the engine. Either command works: the first goes through the top-level CMake option, the second configures the sycl/ project directly.

source /opt/intel/oneapi/setvars.sh
cmake -S . -B build-sycl -G Ninja -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DSTRATA_ENABLE_SYCL=ON
#   or: cmake -S sycl -B build-sycl -G Ninja -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
cmake --build build-sycl --target strata

Options:

  • -DSTRATA_SYCL_AOT=bmg-g31 (Arc Pro B70) or bmg-g21 (B580 / B570 / Pro B60) compiles the GPU code ahead of time. This needs ocloc (Intel's intel-ocloc package). Without it, the first start JIT-compiles every kernel, which takes about 47 s.
  • -DSTRATA_SYCL_PARITY=OFF skips the kernel tests (on by default). Run them with ctest --test-dir build-sycl on the card.

setup_intel.py looks for build-sycl-aot/strata or build-sycl/strata in the checkout. With the top-level option the engine is at build-sycl/sycl/strata, so either use -S sycl or set STRATA_SYCL_BIN.

Setup and running

./setup.sh --backend sycl [setup's usual options, e.g. --model IQ2_XS --context 32768]

This prints the experimental warning and continues with sycl/setup_intel.py. That script finds the Arc in sysfs, uses the SYCL engine you built, and writes the config and run-<model>.sh. It still downloads and packs the model the usual way. To run the engine by hand (no Docker), see "How to run it by hand" in INTEL.md.

Things that matter on an Arc (details in INTEL.md):

  • Do not ask for more VRAM than the card has. On the xe driver, an allocation past VRAM can push buffers into RAM until the machine runs out of memory and stalls. Leave about 1.5 GB free.
  • SYCL_CACHE_PERSISTENT=0: the persistent JIT cache crashed on Xe2 during the first compile.
  • Two cards: ONEAPI_DEVICE_SELECTOR=level_zero:* (the image pins level_zero:0; strata-sycl.sh now passes the variable through) and --layer-split.
  • Arc Pro B60: the PCI id is 8086:e211 (lspci -nn, the kernel's xe id list files it with the BMG-G21 cards), sycl-ls prints Intel(R) Arc(TM) Pro B60 Graphics 20.1.0, and ocloc ids bmg-g21 prints 20.1.0, so -DSTRATA_SYCL_AOT=bmg-g21 is the right target. setup_intel.py knows both B60 ids, e211 and e221 (both seen on B60 cards). On a --layer-split the startup line "N experts are neither in VRAM nor mirrored" counts the other card's layers; the lines 100% of the experts resident that follow are the ones to read. Set STRATA_MIRROR_MIB=0 there, or the pinned mirror is allocated and not used.
  • setvars.sh and set -u: source /opt/intel/oneapi/setvars.sh in a shell with set -u stops at OCL_ICD_FILENAMES: unbound variable (oneAPI 2026.1.1). Source it before set -u, or run set +u around it.
  • Without Docker: sycl/serve/strata-sycl.sh needs Docker. Natively, source setvars.sh, export SYCL_CACHE_PERSISTENT=0, ZES_ENABLE_SYSMAN=1 and STRATA_VERIFY_DEVICE_PLAN=1, then run build-sycl-aot/strata or sycl/serve/server_intel.py with an exe that does this. A normal user is not in the render group on Ubuntu, and then sycl-ls shows only the CPU device.
  • STRATA_VERIFY_NO_HOST=1 (set by strata-sycl.sh) is only valid when every expert is in VRAM. On smaller cards that path is the one that has hung, and #667 found the likely reason: the GPU does not see the CPU's flag stores without a system fence.

Windows

There is no Windows path yet. setup --backend sycl on Windows stops and points here. oneAPI exists for Windows, but sycl/CMakeLists.txt uses GCC-style flags (-mavx512f, -fp-model=precise, -qmkl) and the runner is a bash/Docker script, so a native Windows build would need work. Nobody has tried it. WSL2 with an Arc has been used by one tester (the B580 row above), but setup cannot detect the card there, because it reads /sys/class/drm, which WSL2 does not have.

Reporting a problem

Open an issue with: the card, the driver version, sycl-ls output, the oneAPI version, the model and flags, and the engine's stderr. Results from real cards are what move this from experimental to supported.