--- title: "nndeploy vs fastDeploy" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/nndeploy-nndeploy-vs-notai-tech-fastdeploy" tools: ["nndeploy-nndeploy", "notai-tech-fastdeploy"] --- # nndeploy vs fastDeploy *GraphCanon updated Sep 20, 2026* ## 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. [nndeploy](https://nndeploy-zh.readthedocs.io/zh-cn/latest/) reports 1.9k GitHub stars, 233 forks, and 23 open issues, last pushed Aug 15, 2026. [fastDeploy](https://github.com/notAI-tech/fastDeploy) has 105 stars, 17 forks, and 0 open issues, last pushed Feb 10, 2026. Figures are from public GitHub metadata via [nndeploy's repository](https://github.com/nndeploy/nndeploy) and [fastDeploy's repository](https://github.com/notAI-tech/fastDeploy). | | [nndeploy](/tools/nndeploy-nndeploy.md) | [fastDeploy](/tools/notai-tech-fastdeploy.md) | | --- | --- | --- | | Tagline | An Easy-to-Use and High-Performance AI Deployment Framework | Deploy DL/ML inference pipelines with minimal extra code. | | Stars | 1,878 | 105 | | Forks | 233 | 17 | | Open issues | 23 | 0 | | Language | C++ | Python | | Adopt for | 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 simplifies ML/DL model deployment focusing on minimal code for inference pipelines. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | Developer Tools, Inference & Serving | Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [nndeploy](/tools/nndeploy-nndeploy.md) | [fastDeploy](/tools/notai-tech-fastdeploy.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Slowing (36%) | | Days since push | 32d | 221d | | Open issues (now) | 23 | 0 | | Stars delta | +18 (30d) | 0 (30d) | | Full report | [trust report](/tools/nndeploy-nndeploy/trust.md) | [trust report](/tools/notai-tech-fastdeploy/trust.md) | ## Decision facts: nndeploy - **Adopt for:** nndeploy provides an easy-to-use and high-performance framework for deploying AI algorithms across various platforms with support for multiple deep learning frameworks. ## Decision facts: fastDeploy - **Pricing:** freemium - - - **Requirements:** - Python is required for running fastDeploy.; - Docker installation is suggested but not mandatory. - **Adopt for:** fastDeploy simplifies ML/DL model deployment focusing on minimal code for inference pipelines. ## Choose when ### 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. ### 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 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 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. ## 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](/tools/nndeploy-nndeploy/alternatives) and [fastDeploy alternatives](/tools/notai-tech-fastdeploy/alternatives) ([nndeploy markdown twin](/tools/nndeploy-nndeploy/alternatives.md), [fastDeploy markdown twin](/tools/notai-tech-fastdeploy/alternatives.md)), 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](/compare/nndeploy-nndeploy-vs-notai-tech-fastdeploy.md) 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](/tools/nndeploy-nndeploy/trust); [fastDeploy trust report](/tools/notai-tech-fastdeploy/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=nndeploy-nndeploy`](/api/graphcanon/graph?tool=nndeploy-nndeploy) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_