System Requirements#

Hardware, software, and network requirements for deploying Dine-In Order Accuracy.

Hardware Requirements#

Development / Single Station#

Component

Specification

CPU

8+ cores

RAM

16 GB min; 64 GB recommended for production / heavy model export workloads

GPU

Intel® Arc™ A770 (16 GB) or equivalent Intel GPU

Storage

50 GB SSD

Production / Multi-Station#

Component

Specification

CPU

16+ cores

RAM

64 GB

GPU

Intel® Data Center GPU (for concurrent validation)

Storage

200 GB NVMe SSD

GPU VRAM guidance: The Qwen2.5-VL-7B INT8 model requires ~8 GB of VRAM. The default cache_size=4 reserves an additional 4 GB VRAM for the KV cache. Total VRAM needed is around 12 GB, which fits in an Intel® Arc™ A770 16 GB. On integrated GPU (iGPU) platforms such as Wildcat Lake and Meteor Lake, the KV cache is drawn from system RAM instead of dedicated VRAM; in such a case, use a smaller value (e.g. CACHE_SIZE=2) to avoid exhausting system RAM. Set export CACHE_SIZE=<N> before running setup_models.sh. For a full per-platform sizing table and step-by-step instructions see ovms-service/README.md — Tuning the KV Cache Size.

Model Export RAM Note: 16 GB system RAM is sufficient for inference-only deployments. For first-time model export (setup_models.sh INT8 quantization), a higher-memory host (48–64 GB recommended) avoids potential OOM and corrupt IR files — export once there and copy ovms-service/models/ to the target system. If you must export on 16 GB, set export CACHE_SIZE=2 first. See ovms-service/README.md — Tuning the KV Cache Size for details.

Software Requirements#

Operating System#

Ubuntu 22.04 LTS is the validated platform (matches the python:3.13-slim base image running on the host GPU driver stack).

Container Runtime#

Software

Minimum Version

Docker Engine

24.0

Docker Compose

V2 (2.20+)

GPU Drivers#

Intel GPU drivers must be installed from packages.intel.com. Verify the GPU is accessible to Docker:

ls /dev/dri/
docker run --rm --device /dev/dri intel/openvino_dev:latest python3 -c \
  "from openvino.runtime import Core; print(Core().available_devices)"

Expected output includes GPU.

Network Requirements#

Port Configuration#

Service

Port

Purpose

Gradio UI

7861

Web interface

REST API

8083

FastAPI endpoints

OVMS VLM

8002

Model inference (external)

Semantic Service

8081

Semantic matching (external)

Metrics Collector

8084

System metrics

Next Steps#