Comparison
nndeploy vs fastDeploy
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 fastDeploy if fastDeploy simplifies ML/DL model deployment focusing on minimal code for inference pipelines.
Markdown twin · nndeploy alternatives · fastDeploy alternatives
GraphCanon updated Sep 20, 2026
13views this month
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Trust & integrity
| Signal | nndeploy | fastDeploy |
|---|---|---|
| Maintenance | Steady (32d since push) As of Sep 17, 2026 · github_public_v1 | Slowing (221d since push) As of Sep 20, 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 20, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Jul 15, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 15, 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
- fastDeploy
- Deploy DL/ML inference pipelines with minimal extra code.
Stars
- nndeploy
- 1.9k
- fastDeploy
- 105
Forks
- nndeploy
- 233
- fastDeploy
- 17
Open issues
- nndeploy
- 23
- fastDeploy
- 0
Language
- nndeploy
- C++
- fastDeploy
- Python
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.
- fastDeploy
- fastDeploy simplifies ML/DL model deployment focusing on minimal code for inference pipelines.
Persona
- nndeploy
- -
- fastDeploy
- -
Runtime
- nndeploy
- -
- fastDeploy
- -
License
- nndeploy
- Apache-2.0
- fastDeploy
- MIT
Last pushed
- nndeploy
- Aug 15, 2026
- fastDeploy
- Feb 10, 2026
Categories
- nndeploy
- Developer Tools, Inference & Serving
- fastDeploy
- Inference & Serving
Trust and health
Maintenance
- nndeploy
- Steady (60%)
- fastDeploy
- Slowing (36%)
Days since push
- nndeploy
- 32d
- fastDeploy
- 221d
Open issues (now)
- nndeploy
- 23
- fastDeploy
- 0
Stars delta
- nndeploy
- +18 (30d)
- fastDeploy
- 0 (30d)
OSV dependency advisories
- nndeploy
- Published findings
- fastDeploy
- No lockfile (source not queried)
Full report
- nndeploy
- Trust report
- fastDeploy
- Trust report
Choose nndeploy if…
- nndeploy is primarily C++; fastDeploy is Python.
- License: nndeploy is Apache-2.0, fastDeploy is MIT.
- 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 fastDeploy if…
- fastDeploy is primarily Python; nndeploy is C++.
- License: fastDeploy is MIT, nndeploy is Apache-2.0.
- Pricing: -.
- Requirements: - Python is required for running fastDeploy.; - Docker installation is suggested but not mandatory..
- Tags unique to fastDeploy: docker, falcon, gevent, gunicorn.
- When you aim to streamline the deployment of TensorFlow Serving, TorchServe, and Triton Inference Server models without extensive coding.
When NOT to use fastDeploy
- Avoid if you are looking for a solution that supports real-time interactive deployments requiring advanced websocket handling beyond fastDeploy's basic capability.
- Not recommended when the project requires heavy customization of deployment scripts, as it emphasizes minimal coding and may restrict flexibility in pipeline configurations.
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 (notAI-tech/fastDeploy) · observed Sep 20, 2026
- GitHub forks (notAI-tech/fastDeploy) · observed Sep 20, 2026
- Last push (notAI-tech/fastDeploy) · observed Feb 10, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: nndeploy 1.9k · fastDeploy 105 (synced Sep 20, 2026).
Common questions
- What is the difference between nndeploy and fastDeploy?
- nndeploy: An Easy-to-Use and High-Performance AI Deployment Framework. fastDeploy: Deploy DL/ML inference pipelines with minimal extra code.. See the comparison table for live GitHub stats and shared categories.
- When should I choose nndeploy over fastDeploy?
- Choose nndeploy over fastDeploy when nndeploy is primarily C++; fastDeploy is Python; License: nndeploy is Apache-2.0, fastDeploy is MIT; 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 fastDeploy over nndeploy?
- Choose fastDeploy over nndeploy when fastDeploy is primarily Python; nndeploy is C++; License: fastDeploy is MIT, nndeploy is Apache-2.0; Pricing: -; Requirements: - Python is required for running fastDeploy.; - Docker installation is suggested but not mandatory.; Tags unique to fastDeploy: docker, falcon, gevent, gunicorn; When you aim to streamline the deployment of TensorFlow Serving, TorchServe, and Triton Inference Server models without extensive coding.
- 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 fastDeploy?
- Avoid if you are looking for a solution that supports real-time interactive deployments requiring advanced websocket handling beyond fastDeploy's basic capability. Not recommended when the project requires heavy customization of deployment scripts, as it emphasizes minimal coding and may restrict flexibility in pipeline configurations.
- Is nndeploy or fastDeploy more popular on GitHub?
- nndeploy has more GitHub stars (1,878 vs 105). Stars measure visibility, not whether either tool fits your constraints.
- Are nndeploy and fastDeploy open source?
- Yes - both are open-source projects on GitHub (nndeploy: Apache-2.0, fastDeploy: MIT).
- Where can I find alternatives to nndeploy or fastDeploy?
- GraphCanon lists graph-backed alternatives at nndeploy alternatives and fastDeploy alternatives (nndeploy markdown twin, fastDeploy 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 fastDeploy?
- nndeploy: Steady. fastDeploy: Slowing. 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 fastDeploy?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: nndeploy trust report; fastDeploy trust report.