Comparison
mxnet vs caffe
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 caffe if caffe is designed for deep learning tasks, especially those involving computer vision, and is written in C++ to ensure efficiency.
Markdown twin · mxnet alternatives · caffe alternatives
GraphCanon updated 3w
Trust & integrity
| Signal | mxnet | caffe |
|---|---|---|
| Maintenance | Archived (1012d since push) As of 3w · github_public_v1 | Dormant (732d 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 | No lockfile (source not queried) 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
- caffe
- Caffe is a fast open framework for deep learning.
Stars
- mxnet
- 21k
- caffe
- 35k
Forks
- mxnet
- 6.7k
- caffe
- 18k
Open issues
- mxnet
- 2.0k
- caffe
- 1.5k
Language
- mxnet
- C++
- caffe
- 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.
- caffe
- Caffe is designed for deep learning tasks, especially those involving computer vision, and is written in C++ to ensure efficiency.
Persona
- mxnet
- -
- caffe
- -
Runtime
- mxnet
- -
- caffe
- -
License
- mxnet
- Apache-2.0
- caffe
- Caffe is available under the BSD 2-Clause license.
Last pushed
- mxnet
- Oct 25, 2023
- caffe
- Jul 31, 2024
Categories
- mxnet
- Model Training
- caffe
- Computer Vision, Model Training
Trust and health
Maintenance
- mxnet
- Archived (8%)
- caffe
- Dormant (18%)
Days since push
- mxnet
- 1012d
- caffe
- 732d
Archived on GitHub
- mxnet
- Yes
- caffe
- No
Open issues (now)
- mxnet
- 2.0k
- caffe
- 1.5k
Full report
- mxnet
- Trust report
- caffe
- Trust report
Choose mxnet if…
- License: mxnet is Apache-2.0, caffe is Other.
- 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 caffe if…
- License: caffe is Other, mxnet is Apache-2.0.
- Pricing: Free to use under open source licensing with no monetary charges..
- Tags unique to caffe: machine-learning, vision.
- Also covers Computer Vision.
- - You need a framework that supports high-performance convolutional networks particularly suited for image classification
When NOT to use caffe
- - Your primary task involves natural language processing rather than computer vision challenges, where specialized frameworks might outperform Caffe
- - You seek a framework that integrates seamlessly with Python for both training and inference, as Caffe relies heavily on C++ for its core operations
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 (BVLC/caffe) · observed Aug 3, 2026
- GitHub forks (BVLC/caffe) · observed Aug 3, 2026
- Last push (BVLC/caffe) · observed Jul 31, 2024
- License file (Other) · observed Aug 3, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: mxnet 21k · caffe 35k (synced Aug 3, 2026).
Common questions
- What is the difference between mxnet and caffe?
- mxnet: Lightweight, Portable, Flexible Distributed/Mobile Deep Learning Framework. caffe: Caffe is a fast open framework for deep learning.. See the comparison table for live GitHub stats and shared categories.
- When should I choose mxnet over caffe?
- Choose mxnet over caffe when License: mxnet is Apache-2.0, caffe is Other; 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 caffe over mxnet?
- Choose caffe over mxnet when License: caffe is Other, mxnet is Apache-2.0; Pricing: Free to use under open source licensing with no monetary charges.; Tags unique to caffe: machine-learning, vision; Also covers Computer Vision; - You need a framework that supports high-performance convolutional networks particularly suited for image classification.
- 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 caffe?
- - Your primary task involves natural language processing rather than computer vision challenges, where specialized frameworks might outperform Caffe - You seek a framework that integrates seamlessly with Python for both training and inference, as Caffe relies heavily on C++ for its core operations
- Is mxnet or caffe more popular on GitHub?
- caffe has more GitHub stars (34,573 vs 20,817). Stars measure visibility, not whether either tool fits your constraints.
- Are mxnet and caffe open source?
- Yes - both are open-source projects on GitHub (mxnet: Apache-2.0, caffe: Other).
- Where can I find alternatives to mxnet or caffe?
- GraphCanon lists graph-backed alternatives at mxnet alternatives and caffe alternatives (mxnet markdown twin, caffe 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 caffe?
- mxnet: Archived. caffe: 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 caffe?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: mxnet trust report; caffe trust report.