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MediaTek NeuroPilot

Vendor: MediaTek

Category: NPU Neural Processor

Architecture: APU (AI Processing Unit)

Introduction​

MediaTek NeuroPilot AI platform for AI acceleration in Dimensity and Kompanio series SoCs. Supports multi-framework fusion (TensorFlow/PyTorch/ONNX), providing heterogeneous computing capabilities.

Specifications​

ModelComputeMemoryInterfaceTDPProcess
Dimensity 940040 TOPS (INT8)LPDDR5X (shared)Integrated SoC10W3nm
Dimensity 930032 TOPS (INT8)LPDDR5T (shared)Integrated SoC8W4nm

Official Website​

Visit Official Website

Driver Downloads​

Linux​

OS Support​

WindowsLinuxmacOSAndroid
❌✅ (Android)❌❌

Version History​

VersionRelease DateDescription
NeuroPilot 9.02024On-device large model 7B inference

Performance Benchmarks​

ModelTaskPerformance Metric
Dimensity 9400NPU TOPS~70 TOPS
Dimensity 9400Camera AIReal-time semantic segmentation
Dimensity 9300On-device LLM7B quantized inference

Pricing​

ModelReference PriceNotes
Dimensity 9400Provided with SoCFlagship phone SoC

Quick Installation​

Android​

MediaTek NeuroPilot is automatically invoked through Android NNAPI. TFLite models directly benefit from NPU acceleration.

# Use NeuroPilot SDK for model optimization
# Obtain from MediaTek Developer Portal

Code Examples​

Python (TFLite Android)​

import tflite_runtime.interpreter as tflite

# Android: Use Dimensity NPU via NNAPI
interpreter = tflite.Interpreter(
model_path="model.tflite",
experimental_delegates=[tflite.load_delegate('libneuropilot_delegate.so')]
)

Architecture Highlights​

  • APU (AI Processing Unit): MediaTek integrated NPU, co-processing AI tasks with CPU/GPU
  • NeuroPilot SDK: Developer toolchain supporting model optimization and deployment
  • On-Device LLM: Dimensity 9400 supports 7B parameter LLM on-device inference

Model Compatibility​

Model/FrameworkSupportNotes
NNAPI✅ NativeAndroid standard
TFLite✅NeuroPilot optimized
On-Device LLM✅7B quantization
Camera AI✅Best for camera scenarios

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