--- title: "clearml vs mlrun" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/clearml-clearml-vs-mlrun-mlrun" tools: ["clearml-clearml", "mlrun-mlrun"] --- # clearml vs mlrun *GraphCanon updated Aug 3, 2026* ## Verdict Pick clearml if clearML is an MLOps LLMOps solution that streamlines AI workloads through comprehensive experiment management, data handling, pipeline orchestration, and model serving under one platform; pick mlrun if mLRun: Open-source MLOps platform for rapid ML application development integrated into CI/CD pipelines using Python. [clearml](https://clear.ml/docs) reports 6.8k GitHub stars, 785 forks, and 573 open issues, last pushed Jul 27, 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 [clearml's repository](https://github.com/clearml/clearml) and [mlrun's repository](https://github.com/mlrun/mlrun). | | [clearml](/tools/clearml-clearml.md) | [mlrun](/tools/mlrun-mlrun.md) | | --- | --- | --- | | Tagline | MLOps/LLMOps solution for CI/CD in AI workloads | MLOps Platform for Building and Managing Continuous ML Applications | | Stars | 6,805 | 1,690 | | Forks | 785 | 315 | | Open issues | 573 | 110 | | Language | Python | Python | | Adopt for | ClearML is an MLOps LLMOps solution that streamlines AI workloads through comprehensive experiment management, data handling, pipeline orchestration, and model serving under one platform. | 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 | Inference & Serving, Model Training | Developer Tools, Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [clearml](/tools/clearml-clearml.md) | [mlrun](/tools/mlrun-mlrun.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 7d | 0d | | Open issues (now) | 573 | 110 | | Full report | [trust report](/tools/clearml-clearml/trust.md) | [trust report](/tools/mlrun-mlrun/trust.md) | ## Decision facts: clearml - **Adopt for:** ClearML is an MLOps LLMOps solution that streamlines AI workloads through comprehensive experiment management, data handling, pipeline orchestration, and model serving under one platform. ## 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 clearml if… - Tags unique to clearml: ai, clearml, control, deep-learning. - When you require a single platform for managing experiments, orchestrating pipelines, and serving models in your AI projects - More GitHub stars (6.8k vs 1.7k) - visibility, not fit. ### 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 clearml - Avoid if you need deep support for languages other than Python since ClearML is primarily built around Python - Consider alternatives if your MLOps needs do not include a centralized orchestration platform, as ClearML emphasizes integrated solutions ## 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 clearml and mlrun? clearml: MLOps/LLMOps solution for CI/CD in AI workloads. 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 clearml over mlrun? Choose clearml over mlrun when Tags unique to clearml: ai, clearml, control, deep-learning; When you require a single platform for managing experiments, orchestrating pipelines, and serving models in your AI projects; More GitHub stars (6.8k vs 1.7k) - visibility, not fit. ### When should I choose mlrun over clearml? Choose mlrun over clearml 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 clearml? Avoid if you need deep support for languages other than Python since ClearML is primarily built around Python Consider alternatives if your MLOps needs do not include a centralized orchestration platform, as ClearML emphasizes integrated solutions ### 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 clearml or mlrun more popular on GitHub? clearml has more GitHub stars (6,805 vs 1,690). Stars measure visibility, not whether either tool fits your constraints. ### Are clearml and mlrun open source? Yes - both are open-source projects on GitHub (clearml: Apache-2.0, mlrun: Apache-2.0). ### Where can I find alternatives to clearml or mlrun? GraphCanon lists graph-backed alternatives at [clearml alternatives](/tools/clearml-clearml/alternatives) and [mlrun alternatives](/tools/mlrun-mlrun/alternatives) ([clearml markdown twin](/tools/clearml-clearml/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/clearml-clearml-vs-mlrun-mlrun.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, clearml or mlrun? clearml: 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 clearml and mlrun? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [clearml trust report](/tools/clearml-clearml/trust); [mlrun trust report](/tools/mlrun-mlrun/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=clearml-clearml`](/api/graphcanon/graph?tool=clearml-clearml) - 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/_