Skip to main content

Intel NPU (AI Boost)

Vendor: Intel

Category: NPU Neural Processor

Architecture: Gaudi NPU Core / Movidius

Introduction

Intel Core Ultra processor built-in NPU (AI Boost) for low-power AI inference acceleration. Supports OpenVINO framework, suitable for AI workloads on thin-and-light laptops and edge devices.

Specifications

ModelComputeMemoryInterfaceTDPProcess
Core Ultra 200V48 TOPS (INT8)LPDDR5X (shared)Integrated SoC17-45WIntel 4
Core Ultra (Meteor Lake)12 TOPS (INT8)LPDDR5X (shared)Integrated SoC28WIntel 4
Movidius Myriad X4 TOPS (INT8)512MB LPDDR4USB 3.01.5W16nm

Official Website

Visit Official Website

Driver Downloads

Windows

Linux

OS Support

WindowsLinuxmacOSAndroid

Version History

VersionRelease DateDescription
OpenVINO 2024.42024Lunar Lake NPU support
OpenVINO 2024.02024-Q1LLM inference optimization

Performance Benchmarks

ModelTaskPerformance Metric
Core Ultra 200VNPU TOPS48 TOPS
Core Ultra (Meteor Lake)NPU TOPS11 TOPS
Movidius Myriad XVision Inference4 TOPS, 1.5W

Pricing

ModelReference PriceNotes
Core Ultra 200VProvided with laptopAI PC laptop
Movidius Myriad X~$69-99USB accelerator stick

Quick Installation

Windows 11

Intel NPU is automatically used through the OpenVINO runtime with the latest drivers installed.

# Install OpenVINO
pip install openvino

# Verify NPU availability
python -c "from openvino import Core; core = Core(); print(core.available_devices)"

Code Examples

Python (OpenVINO NPU)

from openvino import Core
from openvino.runtime import Model

# Detect NPU device
core = Core()
print(f"Available devices: {core.available_devices}") # Contains 'NPU'

# Load and compile model to NPU
model = core.read_model("model.xml")
compiled = core.compile_model(model, "NPU")

# Inference
output = compiled(input_data)

Architecture Highlights

  • Intel NPU Core: Low-power NPU core based on Gaudi technology, oriented toward daily AI tasks on AI PCs
  • Movidius VPU: Independent VPU for edge vision inference, suitable for cameras/robots
  • OpenVINO: Intel unified inference framework, automatically selecting the best CPU/GPU/NPU backend

Model Compatibility

Model/FrameworkSupportNotes
OpenVINO✅ NativeBest support
ONNX✅ ConvertOpenVINO direct load
PyTorch✅ ExportConvert ONNX → OpenVINO
Small LLMsOpenVINO + NPU acceleration
Speech/VisionMovidius vision optimized

If you're evaluating alternatives, the following products may also fit your scenario: