--- title: "mlflow vs mlrun" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/mlflow-mlflow-vs-mlrun-mlrun" tools: ["mlflow-mlflow", "mlrun-mlrun"] --- # mlflow vs mlrun *GraphCanon updated Aug 20, 2026* ## Verdict Pick mlflow if mLflow is an open-source platform that offers comprehensive capabilities for managing, deploying, and monitoring machine learning models as well as large language models (LLMs) and AI agents. MLflow supports various use,; pick mlrun if mLRun: Open-source MLOps platform for rapid ML application development integrated into CI/CD pipelines using Python. [mlflow](https://mlflow.org) reports 28k GitHub stars, 6.2k forks, and 2.1k open issues, last pushed Aug 20, 2026. [mlrun](https://mlrun.org) has 1.7k stars, 315 forks, and 110 open issues, last pushed Aug 2, 2026. Figures are from public GitHub metadata via [mlflow's repository](https://github.com/mlflow/mlflow) and [mlrun's repository](https://github.com/mlrun/mlrun). | | [mlflow](/tools/mlflow-mlflow.md) | [mlrun](/tools/mlrun-mlrun.md) | | --- | --- | --- | | Tagline | AI engineering platform for debugging, evaluating, monitoring, and optimizing AI applications | MLOps Platform for Building and Managing Continuous ML Applications | | Stars | 27,591 | 1,690 | | Forks | 6,189 | 315 | | Open issues | 2,054 | 110 | | Language | Python | Python | | Adopt for | MLflow is an open-source platform that offers comprehensive capabilities for managing, deploying, and monitoring machine learning models as well as large language models (LLMs) and AI agents. MLflow supports various use, | MLRun: Open-source MLOps platform for rapid ML application development integrated into CI/CD pipelines using Python. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Evaluation & Observability, Inference & Serving, Model Training | Developer Tools, Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [mlflow](/tools/mlflow-mlflow.md) | [mlrun](/tools/mlrun-mlrun.md) | | --- | --- | --- | | Open issues (now) | 2.1k | 110 | | Stars delta | +476 (30d) | Unknown | | Open issues delta | -22 (30d) | Unknown | | Full report | [trust report](/tools/mlflow-mlflow/trust.md) | [trust report](/tools/mlrun-mlrun/trust.md) | ## Decision facts: mlflow - **Adopt for:** MLflow is an open-source platform that offers comprehensive capabilities for managing, deploying, and monitoring machine learning models as well as large language models (LLMs) and AI agents. MLflow supports various use, ## Decision facts: mlrun - **Adopt for:** MLRun: Open-source MLOps platform for rapid ML application development integrated into CI/CD pipelines using Python. ## Choose when ### Choose mlflow if… - Tags unique to mlflow: agentops, agents, ai-governance, evaluation. - Also covers Evaluation & Observability. - - Use when you're working with a diverse range of environments like local or cloud platforms because MLflow is **vendor-neutral**. ### Choose mlrun if… - Tags unique to mlrun: ci-cd, machine learning pipelines, mlops, serverless functions. - Also covers Developer Tools. - Requires seamless integration of ML workflows into existing CI/CD environments ## When NOT to use mlflow - - Avoid if your organization has strong preferences for proprietary solutions with advanced features not available in the open-source domain. - - Not recommended for users who prefer a fully managed service without self-hosting options, as competitors like Databricks or Azure ML offer integrated services tailored for their cloud environments. ## When NOT to use mlrun - Lacks requirement for serverless function deployment with auto-scaling capabilities - CI/CD integration is not a priority or already fully catered to by alternative tools ## Common questions ### What is the difference between mlflow and mlrun? mlflow: AI engineering platform for debugging, evaluating, monitoring, and optimizing AI applications. mlrun: MLOps Platform for Building and Managing Continuous ML Applications. See the comparison table for live GitHub stats and shared categories. ### When should I choose mlflow over mlrun? Choose mlflow over mlrun when Tags unique to mlflow: agentops, agents, ai-governance, evaluation; Also covers Evaluation & Observability; - Use when you're working with a diverse range of environments like local or cloud platforms because MLflow is **vendor-neutral**. ### When should I choose mlrun over mlflow? Choose mlrun over mlflow when Tags unique to mlrun: ci-cd, machine learning pipelines, mlops, serverless functions; Also covers Developer Tools; Requires seamless integration of ML workflows into existing CI/CD environments. ### When should I avoid mlflow? - Avoid if your organization has strong preferences for proprietary solutions with advanced features not available in the open-source domain. - Not recommended for users who prefer a fully managed service without self-hosting options, as competitors like Databricks or Azure ML offer integrated services tailored for their cloud environments. ### When should I avoid mlrun? Lacks requirement for serverless function deployment with auto-scaling capabilities CI/CD integration is not a priority or already fully catered to by alternative tools ### Is mlflow or mlrun more popular on GitHub? mlflow has more GitHub stars (27,591 vs 1,690). Stars measure visibility, not whether either tool fits your constraints. ### Are mlflow and mlrun open source? Yes - both are open-source projects on GitHub (mlflow: Apache-2.0, mlrun: Apache-2.0). ### Where can I find alternatives to mlflow or mlrun? GraphCanon lists graph-backed alternatives at [mlflow alternatives](/tools/mlflow-mlflow/alternatives) and [mlrun alternatives](/tools/mlrun-mlrun/alternatives) ([mlflow markdown twin](/tools/mlflow-mlflow/alternatives.md), [mlrun markdown twin](/tools/mlrun-mlrun/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/mlflow-mlflow-vs-mlrun-mlrun.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, mlflow or mlrun? mlflow: Very active. mlrun: 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 mlflow and mlrun? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [mlflow trust report](/tools/mlflow-mlflow/trust); [mlrun trust report](/tools/mlrun-mlrun/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=mlflow-mlflow`](/api/graphcanon/graph?tool=mlflow-mlflow) - 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/_