Comparison
nndeploy vs ncnn
Verdict
Pick nndeploy if nndeploy provides an easy-to-use and high-performance framework for deploying AI algorithms across various platforms with support for multiple deep learning frameworks; pick ncnn if ncnn is a high-performance framework for deep learning inference on mobile platforms written in C++, supporting conversion from multiple DL frameworks via pnnx.
Markdown twin · nndeploy alternatives · ncnn alternatives
GraphCanon updated Sep 20, 2026
11views this month
Trust & integrity
| Signal | nndeploy | ncnn |
|---|---|---|
| Maintenance | Steady (32d since push) As of Sep 17, 2026 · github_public_v1 | Very active (1d since push) As of Sep 4, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 17, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 4, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Jul 15, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · 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
- nndeploy
- An Easy-to-Use and High-Performance AI Deployment Framework
- ncnn
- High-performance neural network inference framework optimized for mobile platforms
Stars
- nndeploy
- 1.9k
- ncnn
- 24k
Forks
- nndeploy
- 233
- ncnn
- 4.5k
Open issues
- nndeploy
- 23
- ncnn
- 1.2k
Language
- nndeploy
- C++
- ncnn
- C++
Adopt for
- nndeploy
- nndeploy provides an easy-to-use and high-performance framework for deploying AI algorithms across various platforms with support for multiple deep learning frameworks.
- ncnn
- ncnn is a high-performance framework for deep learning inference on mobile platforms written in C++, supporting conversion from multiple DL frameworks via pnnx.
Persona
- nndeploy
- -
- ncnn
- -
Runtime
- nndeploy
- -
- ncnn
- -
License
- nndeploy
- Apache-2.0
- ncnn
- Other, details not specified within the provided repository content.
Last pushed
- nndeploy
- Aug 15, 2026
- ncnn
- Sep 2, 2026
Categories
- nndeploy
- Developer Tools, Inference & Serving
- ncnn
- Inference & Serving
Trust and health
Maintenance
- nndeploy
- Steady (60%)
- ncnn
- Very active (96%)
Days since push
- nndeploy
- 32d
- ncnn
- 1d
Open issues (now)
- nndeploy
- 23
- ncnn
- 1.2k
Stars delta
- nndeploy
- +18 (30d)
- ncnn
- +140 (30d)
Open issues delta
- nndeploy
- 0 (30d)
- ncnn
- +30 (30d)
OSV dependency advisories
- nndeploy
- Published findings
- ncnn
- No lockfile (source not queried)
Full report
- nndeploy
- Trust report
- ncnn
- Trust report
Shared compatibility
- Python · nndeploy: Python runtime · ncnn: Python runtime
Choose nndeploy if…
- License: nndeploy is Apache-2.0, ncnn is Other.
- Tags unique to nndeploy: ai, ascend, deployment, diffusers.
- Also covers Developer Tools.
- If you need a tool that supports both Python and C++ custom nodes, integrating well into visual workflow design.
When NOT to use nndeploy
- Do not use if your project only requires low-level access to hardware without the need for a high-level interface like nndeploy offers.
- If you're working exclusively on platforms or frameworks unsupported by nndeploy, such as certain proprietary or non-mainstream inference engines.
Choose ncnn if…
- License: ncnn is Other, nndeploy is Apache-2.0.
- Requirements: Requires pnnx for exporting PyTorch models to ncnn..
- Tags unique to ncnn: android, arm-neon, artificial-intelligence, caffe.
- For users requiring fast inference speeds optimized for mobile devices such as Android and iOS.
When NOT to use ncnn
- If working in an environment where GPU acceleration on desktop or server is more beneficial than CPU efficiency.
- For tasks that demand extensive training within the framework itself, as ncnn focuses on inference rather than training capabilities.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (nndeploy/nndeploy) · observed Sep 20, 2026
- GitHub forks (nndeploy/nndeploy) · observed Sep 20, 2026
- Last push (nndeploy/nndeploy) · observed Aug 15, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (Tencent/ncnn) · observed Sep 20, 2026
- GitHub forks (Tencent/ncnn) · observed Sep 20, 2026
- Last push (Tencent/ncnn) · observed Sep 2, 2026
- License file (Other) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: nndeploy 1.9k · ncnn 24k (synced Sep 20, 2026).
Common questions
- What is the difference between nndeploy and ncnn?
- nndeploy: An Easy-to-Use and High-Performance AI Deployment Framework. ncnn: High-performance neural network inference framework optimized for mobile platforms. See the comparison table for live GitHub stats and shared categories.
- When should I choose nndeploy over ncnn?
- Choose nndeploy over ncnn when License: nndeploy is Apache-2.0, ncnn is Other; Tags unique to nndeploy: ai, ascend, deployment, diffusers; Also covers Developer Tools; If you need a tool that supports both Python and C++ custom nodes, integrating well into visual workflow design.
- When should I choose ncnn over nndeploy?
- Choose ncnn over nndeploy when License: ncnn is Other, nndeploy is Apache-2.0; Requirements: Requires pnnx for exporting PyTorch models to ncnn.; Tags unique to ncnn: android, arm-neon, artificial-intelligence, caffe; For users requiring fast inference speeds optimized for mobile devices such as Android and iOS.
- When should I avoid nndeploy?
- Do not use if your project only requires low-level access to hardware without the need for a high-level interface like nndeploy offers. If you're working exclusively on platforms or frameworks unsupported by nndeploy, such as certain proprietary or non-mainstream inference engines.
- When should I avoid ncnn?
- If working in an environment where GPU acceleration on desktop or server is more beneficial than CPU efficiency. For tasks that demand extensive training within the framework itself, as ncnn focuses on inference rather than training capabilities.
- Is nndeploy or ncnn more popular on GitHub?
- ncnn has more GitHub stars (23,784 vs 1,878). Stars measure visibility, not whether either tool fits your constraints.
- Are nndeploy and ncnn open source?
- Yes - both are open-source projects on GitHub (nndeploy: Apache-2.0, ncnn: Other).
- Where can I find alternatives to nndeploy or ncnn?
- GraphCanon lists graph-backed alternatives at nndeploy alternatives and ncnn alternatives (nndeploy markdown twin, ncnn 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, nndeploy or ncnn?
- nndeploy: Steady. ncnn: Very active. 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 nndeploy and ncnn?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: nndeploy trust report; ncnn trust report.