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mindspore

mindspore-ai/mindspore

An open-source deep learning framework for mobile, edge and cloud scenarios.

GitHub Website

GraphCanon updated 2w · GitHub synced 2w

4.7k stars751 forksLast push 2y C++ Apache-2.0

Decision brief

MindSpore's core strengths lie in its flexibility across Ascend910, GPU CUDA 10.1, and CPU setups on multiple OSes; it excels in mobile, edge, and cloud scenarios.

Good fit when

When working with Huawei's Ascend hardware like Ascend910
For cross-platform compatibility (Ubuntu, CentOS, Windows-x86)

Avoid when

Avoid if only NVIDIA GPUs without CUDA 10.1 support are available
Not ideal for users requiring non-LINUX (excluding Windows) environments beyond specified Ubuntu/CentOS/x86 versions

Observed Jul 12, 2026 · Source: enrich:decision_facts

mindspore alternatives Trust report

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Maintenance and security

Full trust report

Maintenance: Dormant (735d since push); As of 2w
Provenance: Not a fork · Organization account; As of 2w
Security (OSV): 103 low (103 low); As of 1mo

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

git clone https://github.com/mindspore-ai/mindspore

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

MindSpore is a flexible training/inference framework that supports various hardware configurations including Ascend910, GPU (CUDA 10.1), and CPU setups on different operating systems like Ubuntu (x86, aarch64) and Windows-x86.

Capability facts

Languages: c++
Source: github.language · Aug 3, 2026

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Aug 3, 2026)

```python import numpy as np

Source link

README

Pip mode method installation

MindSpore offers build options across multiple backends:

Hardware Platform	Operating System	Status
Ascend910	Ubuntu-x86	✔️
	Ubuntu-aarch64	✔️
	EulerOS-aarch64	✔️
	CentOS-x86	✔️
	CentOS-aarch64	✔️
GPU CUDA 10.1	Ubuntu-x86	✔️
CPU	Ubuntu-x86	✔️
	Ubuntu-aarch64	✔️
	Windows-x86	✔️

For installation using pip, take CPU and Ubuntu-x86 build version as an example:

Download whl from MindSpore download page, and install the package.

pip install https://ms-release.obs.cn-north-4.myhuaweicloud.com/1.2.0-rc1/MindSpore/cpu/ubuntu_x86/mindspore-1.2.0rc1-cp37-cp37m-linux_x86_64.whl

Run the following command to verify the install.

import numpy as np
import mindspore.context as context
import mindspore.nn as nn
from mindspore import Tensor
from mindspore.ops import operations as P

context.set_context(mode=context.GRAPH_MODE, device_target="CPU")

class Mul(nn.Cell):
    def __init__(self):
        super(Mul, self).__init__()
        self.mul = P.Mul()

    def construct(self, x, y):
        return self.mul(x, y)

x = Tensor(np.array([1.0, 2.0, 3.0]).astype(np.float32))
y = Tensor(np.array([4.0, 5.0, 6.0]).astype(np.float32))

mul = Mul()
print(mul(x, y))

[ 4. 10. 18.]

Use pip mode method to install MindSpore in different environments. Refer to the following documents.

Source code compilation installation

Use the source code compilation method to install MindSpore in different environments. Refer to the following documents.

Docker Image

MindSpore docker image is hosted on Docker Hub, currently the containerized build options are supported as follows:

Hardware Platform	Docker Image Repository	Tag	Description
CPU	`mindspore/mindspore-cpu`	`x.y.z`	Production environment with pre-installed MindSpore `x.y.z` CPU release.
		`devel`	Development environment provided to build MindSpore (with `CPU` backend) from the source, refer to https://www.mindspore.cn/install/en for installation details.
		`runtime`	Runtime environment provided to install MindSpore binary package with `CPU` backend.
GPU	`mindspore/mindspore-gpu`	`x.y.z`	Production environment with pre-installed MindSpore `x.y.z` GPU release.
		`devel`	Development environment provided to build MindSpore (with `GPU CUDA10.1` backend) from the source, refer to https://www.mindspore.cn/install/en for installation details.
		`runtime`	Runtime environment provided to install MindSpore binary package with `GPU CUDA10.1` backend.

NOTICE: For GPU devel docker image, it's NOT s

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