Comparison
mxnet vs mindspore
Verdict
Pick mxnet if apache MXNet is a deep learning framework that prioritizes efficiency and flexibility, allowing for the mix of symbolic and imperative programming techniques; pick mindspore if 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.
Markdown twin · mxnet alternatives · mindspore alternatives
GraphCanon updated 3w
Trust & integrity
| Signal | mxnet | mindspore |
|---|---|---|
| Maintenance | Archived (1012d since push) As of 3w · github_public_v1 | Dormant (735d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Organization account As of 3w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | Published findings As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- mxnet
- Lightweight, Portable, Flexible Distributed/Mobile Deep Learning Framework
- mindspore
- An open-source deep learning framework for mobile, edge and cloud scenarios.
Stars
- mxnet
- 21k
- mindspore
- 4.7k
Forks
- mxnet
- 6.7k
- mindspore
- 751
Open issues
- mxnet
- 2.0k
- mindspore
- 250
Language
- mxnet
- C++
- mindspore
- C++
Adopt for
- mxnet
- Apache MXNet is a deep learning framework that prioritizes efficiency and flexibility, allowing for the mix of symbolic and imperative programming techniques.
- mindspore
- 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.
Persona
- mxnet
- -
- mindspore
- -
Runtime
- mxnet
- -
- mindspore
- -
License
- mxnet
- Apache-2.0
- mindspore
- Apache-2.0
Last pushed
- mxnet
- Oct 25, 2023
- mindspore
- Jul 29, 2024
Categories
- mxnet
- Model Training
- mindspore
- Inference & Serving, Model Training
Trust and health
Maintenance
- mxnet
- Archived (8%)
- mindspore
- Dormant (18%)
Days since push
- mxnet
- 1012d
- mindspore
- 735d
Archived on GitHub
- mxnet
- Yes
- mindspore
- No
Open issues (now)
- mxnet
- 2.0k
- mindspore
- 250
OSV dependency advisories
- mxnet
- No lockfile (source not queried)
- mindspore
- Published findings
Full report
- mxnet
- Trust report
- mindspore
- Trust report
Shared compatibility
- Python · mxnet: Python runtime · mindspore: Python runtime
Choose mxnet if…
- Pricing: Open-source, open-access framework with advanced services potentially requiring proprietary add-ons or cloud service costs..
- Requirements: MXNet is known for its lightweight nature and efficient memory management, making it suitable for deployment on various hardware configurations..
- Tags unique to mxnet: auto hybridization, distributed-computing, flexible, lightweight.
- You prefer to mix symbolic and imperative programming styles in your deep learning projects for maximum productivity and performance.
When NOT to use mxnet
- If you require a framework with more out-of-the-box models and easier-to-use libraries, since MXNet focuses on flexibility and efficiency over convenience in pre-built functionalities.
- You are focusing exclusively on one particular programming language (other than Python), as while MXNet supports multiple languages, most community support and updates center around its Python API.
Choose mindspore if…
- Tags unique to mindspore: ascend910, cpu-support, gpu-support, inference framework.
- Also covers Inference & Serving.
- When working with Huawei's Ascend hardware like Ascend910
When NOT to use mindspore
- 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
- If development primarily targets hardware not covered by MindSpore's Ascend, CUDA, or CPU setups
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (apache/mxnet) · observed Aug 3, 2026
- GitHub forks (apache/mxnet) · observed Aug 3, 2026
- Last push (apache/mxnet) · observed Oct 25, 2023
- License file (Apache-2.0) · observed Aug 3, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (mindspore-ai/mindspore) · observed Aug 3, 2026
- GitHub forks (mindspore-ai/mindspore) · observed Aug 3, 2026
- Last push (mindspore-ai/mindspore) · observed Jul 29, 2024
- License file (Apache-2.0) · observed Aug 3, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: mxnet 21k · mindspore 4.7k (synced Aug 3, 2026).
Common questions
- What is the difference between mxnet and mindspore?
- mxnet: Lightweight, Portable, Flexible Distributed/Mobile Deep Learning Framework. mindspore: An open-source deep learning framework for mobile, edge and cloud scenarios.. See the comparison table for live GitHub stats and shared categories.
- When should I choose mxnet over mindspore?
- Choose mxnet over mindspore when Pricing: Open-source, open-access framework with advanced services potentially requiring proprietary add-ons or cloud service costs.; Requirements: MXNet is known for its lightweight nature and efficient memory management, making it suitable for deployment on various hardware configurations.; Tags unique to mxnet: auto hybridization, distributed-computing, flexible, lightweight; You prefer to mix symbolic and imperative programming styles in your deep learning projects for maximum productivity and performance.
- When should I choose mindspore over mxnet?
- Choose mindspore over mxnet when Tags unique to mindspore: ascend910, cpu-support, gpu-support, inference framework; Also covers Inference & Serving; When working with Huawei's Ascend hardware like Ascend910.
- When should I avoid mxnet?
- If you require a framework with more out-of-the-box models and easier-to-use libraries, since MXNet focuses on flexibility and efficiency over convenience in pre-built functionalities. You are focusing exclusively on one particular programming language (other than Python), as while MXNet supports multiple languages, most community support and updates center around its Python API.
- When should I avoid mindspore?
- 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 If development primarily targets hardware not covered by MindSpore's Ascend, CUDA, or CPU setups
- Is mxnet or mindspore more popular on GitHub?
- mxnet has more GitHub stars (20,817 vs 4,699). Stars measure visibility, not whether either tool fits your constraints.
- Are mxnet and mindspore open source?
- Yes - both are open-source projects on GitHub (mxnet: Apache-2.0, mindspore: Apache-2.0).
- Where can I find alternatives to mxnet or mindspore?
- GraphCanon lists graph-backed alternatives at mxnet alternatives and mindspore alternatives (mxnet markdown twin, mindspore markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, mxnet or mindspore?
- mxnet: Archived. mindspore: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for mxnet and mindspore?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: mxnet trust report; mindspore trust report.