System Requirements#

Hardware Requirements#

  • CPU: x86_64. Intel Core Ultra (Meteor Lake) or newer is recommended. Older Intel Core / Xeon processors will run the service but may be slower on OpenVINO inference paths.

  • Memory: 16 GB RAM minimum. 32 GB recommended when running ASR and sentiment together, when using larger Whisper variants, or when keeping multiple sessions warm.

  • Disk: 20 GB free SSD space recommended for model assets, the Hugging Face cache, temporary audio chunks, and per-session storage. NVMe is preferred for faster first-run model export.

  • GPU (optional): Intel integrated GPU (Meteor Lake or newer iGPU) or a supported discrete GPU exposed via /dev/dri for the OpenVINO GPU device path.

  • NPU (optional): Intel NPU on Meteor Lake or newer, exposed via a host NPU device node and used by setting ACCEL_MOUNT_PATH to that node (commonly /dev/accel/accel0 on Meteor Lake systems), plus the ZE_ENABLE_ALT_DRIVERS=libze_intel_npu.so runtime variable.

  • Microphone (optional): ALSA-compatible capture device if you intend to list devices via GET /devices or pass /dev/snd into the container.

Device

Minimum

Recommended

CPU

x86_64

Intel Core Ultra (Meteor Lake) or newer

Memory

16 GB RAM

32 GB RAM

Disk

20 GB free SSD space

NVMe storage

GPU (optional)

Not applicable

Intel integrated GPU (Meteor Lake or newer iGPU) or a supported discrete GPU exposed via /dev/dri

NPU (optional)

Not applicable

Intel NPU on Meteor Lake or newer exposed via a host NPU device node (commonly /dev/accel/accel0)

Microphone (optional)

Not applicable

ALSA-compatible capture device with /dev/snd access when needed

Software Requirements#

Operating System#

  • Ubuntu 22.04 LTS (validated) or a compatible Linux distribution with a recent kernel.

  • For container deployment: Docker Engine and Docker Compose v2.

  • For GPU acceleration on Linux: Intel/OpenVINO host GPU runtime (e.g. intel-opencl-icd, level-zero) installed on the host. This is a separate prerequisite from the Python dependencies.

Host Packages (Standalone Run)#

The standalone path additionally requires:

sudo apt-get update
sudo apt-get install -y ffmpeg alsa-utils libsndfile1

Python#

  • Python 3.10 or newer.

  • Dependencies installed from requirements.txt.

Hugging Face Access (For Speaker Diarization)#

If you plan to enable speaker diarization in config.yaml, you must have:

If speaker diarization is not enabled in config.yaml, HF_TOKEN is not required.

Network Requirements#

  • Outbound internet access on first run to download model assets from Hugging Face, unless models are pre-staged under models/ and the cache.

  • Inbound access to TCP port 8010 (default) for API clients.