--- title: "zenml vs zeno" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/zenml-io-zenml-vs-zeno-ml-zeno" tools: ["zenml-io-zenml", "zeno-ml-zeno"] --- # zenml vs zeno *GraphCanon updated Sep 28, 2026* ## Verdict Pick zenml if zenML is a comprehensive AI development platform that supports pipelines, agents, and operations from training to deployment, making it suitable for teams that require a unified solution for their AI lifecycle management; pick zeno if zeno combines Python API with an interactive UI for evaluating ML models across various tasks. [zenml](https://zenml.io) reports 5.6k GitHub stars, 656 forks, and 167 open issues, last pushed Sep 18, 2026. [zeno](https://zenoml.com) has 214 stars, 11 forks, and 45 open issues, last pushed Oct 5, 2023. Figures are from public GitHub metadata via [zenml's repository](https://github.com/zenml-io/zenml) and [zeno's repository](https://github.com/zeno-ml/zeno). | | [zenml](/tools/zenml-io-zenml.md) | [zeno](/tools/zeno-ml-zeno.md) | | --- | --- | --- | | Tagline | One AI Platform from Pipelines to Agents | AI Data Management & Evaluation Platform | | Stars | 5,582 | 214 | | Forks | 656 | 11 | | Open issues | 167 | 45 | | Language | Python | Svelte | | Adopt for | ZenML is a comprehensive AI development platform that supports pipelines, agents, and operations from training to deployment, making it suitable for teams that require a unified solution for their AI lifecycle management | Zeno combines Python API with an interactive UI for evaluating ML models across various tasks. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | AI Agents, Developer Tools, Inference & Serving, Model Training | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [zenml](/tools/zenml-io-zenml.md) | [zeno](/tools/zeno-ml-zeno.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Archived (8%) | | Days since push | 0d | 1088d | | Archived on GitHub | No | Yes | | Open issues (now) | 167 | 45 | | Stars delta | +88 (30d) | 0 (30d) | | Open issues delta | +20 (30d) | 0 (30d) | | Full report | [trust report](/tools/zenml-io-zenml/trust.md) | [trust report](/tools/zeno-ml-zeno/trust.md) | ## Shared compatibility - **Python**: [zenml](/tools/zenml-io-zenml.md) - Python runtime; [zeno](/tools/zeno-ml-zeno.md) - Python runtime ## Decision facts: zenml - **Pricing:** freemium - Open-source under the Apache-2.0 license, with potential enterprise features or support available for a fee - **Requirements:** Min 4 GB RAM; Requires Docker; Installation of ZenML with server capabilities requires additional dependencies - **Adopt for:** ZenML is a comprehensive AI development platform that supports pipelines, agents, and operations from training to deployment, making it suitable for teams that require a unified solution for their AI lifecycle management - **License detail:** Apache-2.0 ## Decision facts: zeno - **Adopt for:** Zeno combines Python API with an interactive UI for evaluating ML models across various tasks. ## Choose when ### Choose zenml if… - zenml is primarily Python; zeno is Svelte. - License: zenml is Apache-2.0, zeno is MIT. - Pricing: Open-source under the Apache-2.0 license, with potential enterprise features or support available for a fee. - Requirements: Min 4 GB RAM; Requires Docker; Installation of ZenML with server capabilities requires additional dependencies. - Tags unique to zenml: agentops, automl, deep-learning, genai. - Also covers AI Agents, Developer Tools, Inference & Serving, Model Training. - zenml ships Docker support for self-hosted deployment. - When you need a unified platform that supports both pipelines and agents, allowing for seamless integration from training to deployment ### Choose zeno if… - zeno is primarily Svelte; zenml is Python. - License: zeno is MIT, zenml is Apache-2.0. - Tags unique to zeno: ai, evaluation-framework. - Also covers Evaluation & Observability. - You need to analyze model performance interactively via a user interface ## When NOT to use zenml - If your project only requires a lightweight pipeline solution without the need for agent management or comprehensive lifecycle operations - When you are looking for a platform that focuses solely on a specific aspect of AI development, such as only model training or only deployment, as ZenML offers a broader range of features that might b ## When NOT to use zeno - Your project requires real-time monitoring capabilities not provided by Zeno's evaluation framework - If you are looking for a specialized tool tailored only to specific data types, like just images or text without the modular versatility of Zeno ## Common questions ### What is the difference between zenml and zeno? zenml: One AI Platform from Pipelines to Agents. zeno: AI Data Management & Evaluation Platform. See the comparison table for live GitHub stats and shared categories. ### When should I choose zenml over zeno? Choose zenml over zeno when zenml is primarily Python; zeno is Svelte; License: zenml is Apache-2.0, zeno is MIT; Pricing: Open-source under the Apache-2.0 license, with potential enterprise features or support available for a fee; Requirements: Min 4 GB RAM; Requires Docker; Installation of ZenML with server capabilities requires additional dependencies; Tags unique to zenml: agentops, automl, deep-learning, genai; Also covers AI Agents, Developer Tools, Inference & Serving, Model Training; zenml ships Docker support for self-hosted deployment; When you need a unified platform that supports both pipelines and agents, allowing for seamless integration from training to deployment. ### When should I choose zeno over zenml? Choose zeno over zenml when zeno is primarily Svelte; zenml is Python; License: zeno is MIT, zenml is Apache-2.0; Tags unique to zeno: ai, evaluation-framework; Also covers Evaluation & Observability; You need to analyze model performance interactively via a user interface. ### When should I avoid zenml? If your project only requires a lightweight pipeline solution without the need for agent management or comprehensive lifecycle operations When you are looking for a platform that focuses solely on a specific aspect of AI development, such as only model training or only deployment, as ZenML offers a broader range of features that might b ### When should I avoid zeno? Your project requires real-time monitoring capabilities not provided by Zeno's evaluation framework If you are looking for a specialized tool tailored only to specific data types, like just images or text without the modular versatility of Zeno ### Is zenml or zeno more popular on GitHub? zenml has more GitHub stars (5,582 vs 214). Stars measure visibility, not whether either tool fits your constraints. ### Are zenml and zeno open source? Yes - both are open-source projects on GitHub (zenml: Apache-2.0, zeno: MIT). ### Where can I find alternatives to zenml or zeno? GraphCanon lists graph-backed alternatives at [zenml alternatives](/tools/zenml-io-zenml/alternatives) and [zeno alternatives](/tools/zeno-ml-zeno/alternatives) ([zenml markdown twin](/tools/zenml-io-zenml/alternatives.md), [zeno markdown twin](/tools/zeno-ml-zeno/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/zenml-io-zenml-vs-zeno-ml-zeno.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, zenml or zeno? zenml: Very active. zeno: Archived. 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 zenml and zeno? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [zenml trust report](/tools/zenml-io-zenml/trust); [zeno trust report](/tools/zeno-ml-zeno/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=zenml-io-zenml`](/api/graphcanon/graph?tool=zenml-io-zenml) - 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/_