OpenViSTAI · Agents · Blockchain · Crypto
Submit a project
Menu
AI Developer Tools & SDKs

Megengine

MegEngine is an open-source deep-learning framework for training and inference, with automatic differentiation, tensor operations, quantization, dynamic-shape and image preprocessing, and inference optimization.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Megengine — OpenViST project profile in AI Developer Tools & SDKs.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use MegEngine when you need a framework that covers model training and inference and want to evaluate its documented deployment targets and Python installation options.

Who it is for

  • Developers building deep-learning models with Python or C++.
  • Teams preparing trained models for inference on documented CPU, GPU, mobile and other deployment targets.

Documented uses

  • Develop and train deep-learning models using automatic differentiation and tensor operations.
  • Apply quantization and preprocessing as part of a model workflow.
  • Prepare models for inference on x86, Arm, CUDA or ROCm environments.
Before you choose

Requirements & limits

The project is open source under the Apache License 2.0. Python installation is documented for Python 3.6–3.9 on specified platforms; source-build instructions are also linked from the repository.

  • Python wheel availability is documented for specific operating systems, architectures, and Python versions; macOS and Android Python installations are CPU-only.
  • The README lists x86, Arm, CUDA and ROCm for inference, while installation and inference support are distinct.
  • CMake and Python binding builds have separate instructions.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Install a documented Python wheel

Install MegEngine from its published pip wheel for a listed Python platform.

Before you start

  • A 64-bit Linux or Windows system, macOS 10.14 or later on CPU, or Android 7 or later on CPU.
  • Python 3.6 to 3.9.
  • Python pip.

Steps

  1. Upgrade pip with the command below.

    Documented command
    python3 -m pip install --upgrade pip

  2. Install MegEngine with the command below.

    Documented command
    python3 -m pip install megengine -f https://megengine.org.cn/whl/mge.html

Expected outcome

The documented pip command requests the MegEngine package from its wheel index.

Guide limitations

  • The README limits Python installation to the listed platforms and versions; it does not provide a wheel-install procedure for every inference target.
Documentation 1 ↗
COMPARE OPTIONS

Compare options for Model inference and serving

These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.

ProjectDocumented purposePlatformAccess and requirements
MegengineDevelop and train deep-learning models using automatic differentiation and tensor operations.Android, CLI, iOS, LinuxThe project is open source under the Apache License 2.0. Python installation is documented for Python 3.6–3.9 on specified platforms; source-build instructions are also linked from the repository.
HyperposeCustomize pose-estimation architectures and datasets.Docker, Linux, macOS, Windows
Multi Task NlpDefine multiple tasks and their data and model settings in a YAML file.Linux, macOS, WindowsThe project is an open-source library under the Apache-2.0 license, distributed through its public GitHub repository.
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
14 October 2026
Original website title
MegEngine/MegEngine · Official homepage title · retained in its source language
How we review sourcesSuggest a correction