--- title: "truss vs fastDeploy" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/basetenlabs-truss-vs-notai-tech-fastdeploy" tools: ["basetenlabs-truss", "notai-tech-fastdeploy"] --- # truss vs fastDeploy *GraphCanon updated Sep 20, 2026* ## Verdict Pick truss if truss, an open-source Python tool designed for serving AI/ML models in production environments with easy-to-use APIs; pick fastDeploy if fastDeploy simplifies ML/DL model deployment focusing on minimal code for inference pipelines. [truss](https://truss.baseten.co) reports 1.2k GitHub stars, 126 forks, and 82 open issues, last pushed Sep 18, 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 [truss's repository](https://github.com/basetenlabs/truss) and [fastDeploy's repository](https://github.com/notAI-tech/fastDeploy). | | [truss](/tools/basetenlabs-truss.md) | [fastDeploy](/tools/notai-tech-fastdeploy.md) | | --- | --- | --- | | Tagline | The simplest way to serve AI/ML models in production | Deploy DL/ML inference pipelines with minimal extra code. | | Stars | 1,203 | 105 | | Forks | 126 | 17 | | Open issues | 82 | 0 | | Language | Python | Python | | Adopt for | Truss, an open-source Python tool designed for serving AI/ML models in production environments with easy-to-use APIs. | fastDeploy simplifies ML/DL model deployment focusing on minimal code for inference pipelines. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | Inference & Serving | Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [truss](/tools/basetenlabs-truss.md) | [fastDeploy](/tools/notai-tech-fastdeploy.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 1d | 221d | | Open issues (now) | 82 | 0 | | Stars delta | +15 (30d) | 0 (30d) | | Open issues delta | +3 (30d) | 0 (30d) | | Full report | [trust report](/tools/basetenlabs-truss/trust.md) | [trust report](/tools/notai-tech-fastdeploy/trust.md) | ## Decision facts: truss - **Adopt for:** Truss, an open-source Python tool designed for serving AI/ML models in production environments with easy-to-use APIs. ## 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 truss if… - Tags unique to truss: artificial-intelligence, easy-to-use, inference-api, inference-server. - - When you seek simplicity in packaging and deploying ML models; Truss aims to stand out as the simplest way compared to its competitors. - More GitHub stars (1.2k vs 105) - visibility, not fit. ### Choose fastDeploy if… - Pricing: -. - Requirements: - Python is required for running fastDeploy.; - Docker installation is suggested but not mandatory.. - Tags unique to fastDeploy: deep-learning, docker, 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 truss - - Avoid if your project requires more complex customization not supported by Truss's straightforward model packaging method. - - Not suitable for teams preferring non-Python environments, as Truss is built predominantly with Python in mind. ## 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 truss and fastDeploy? truss: The simplest way to serve AI/ML models in production. 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 truss over fastDeploy? Choose truss over fastDeploy when Tags unique to truss: artificial-intelligence, easy-to-use, inference-api, inference-server; - When you seek simplicity in packaging and deploying ML models; Truss aims to stand out as the simplest way compared to its competitors; More GitHub stars (1.2k vs 105) - visibility, not fit. ### When should I choose fastDeploy over truss? Choose fastDeploy over truss when Pricing: -; Requirements: - Python is required for running fastDeploy.; - Docker installation is suggested but not mandatory.; Tags unique to fastDeploy: deep-learning, docker, 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 truss? - Avoid if your project requires more complex customization not supported by Truss's straightforward model packaging method. - Not suitable for teams preferring non-Python environments, as Truss is built predominantly with Python in mind. ### 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 truss or fastDeploy more popular on GitHub? truss has more GitHub stars (1,203 vs 105). Stars measure visibility, not whether either tool fits your constraints. ### Are truss and fastDeploy open source? Yes - both are open-source projects on GitHub (truss: MIT, fastDeploy: MIT). ### Where can I find alternatives to truss or fastDeploy? GraphCanon lists graph-backed alternatives at [truss alternatives](/tools/basetenlabs-truss/alternatives) and [fastDeploy alternatives](/tools/notai-tech-fastdeploy/alternatives) ([truss markdown twin](/tools/basetenlabs-truss/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/basetenlabs-truss-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, truss or fastDeploy? truss: Very active. 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 truss and fastDeploy? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [truss trust report](/tools/basetenlabs-truss/trust); [fastDeploy trust report](/tools/notai-tech-fastdeploy/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=basetenlabs-truss`](/api/graphcanon/graph?tool=basetenlabs-truss) - 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/_