Comparison
clearml vs zenml
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 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.
Markdown twin · clearml alternatives · zenml alternatives
GraphCanon updated Sep 27, 2026
9views this month
Trust & integrity
| Signal | clearml | zenml |
|---|---|---|
| Maintenance | Very active (3d since push) As of Sep 27, 2026 · github_public_v1 | Very active (0d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 27, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- clearml
- MLOps/LLMOps solution for CI/CD in AI workloads
- zenml
- One AI Platform from Pipelines to Agents
Stars
- clearml
- 6.9k
- zenml
- 5.6k
Forks
- clearml
- 802
- zenml
- 656
Open issues
- clearml
- 526
- zenml
- 167
Language
- clearml
- Python
- zenml
- Python
Adopt for
- clearml
- ClearML is an MLOps LLMOps solution that streamlines AI workloads through comprehensive experiment management, data handling, pipeline orchestration, and model serving under one platform.
- zenml
- 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
Persona
- clearml
- -
- zenml
- -
Runtime
- clearml
- -
- zenml
- -
License
- clearml
- Apache-2.0
- zenml
- Apache-2.0
Last pushed
- clearml
- Sep 23, 2026
- zenml
- Sep 18, 2026
Categories
- clearml
- Inference & Serving, Model Training
- zenml
- AI Agents, Developer Tools, Inference & Serving, Model Training
Trust and health
Days since push
- clearml
- 3d
- zenml
- 0d
Open issues (now)
- clearml
- 526
- zenml
- 167
Stars delta
- clearml
- +86 (30d)
- zenml
- +88 (30d)
Open issues delta
- clearml
- -47 (30d)
- zenml
- +20 (30d)
OSV dependency advisories
- clearml
- Published findings
- zenml
- No lockfile (source not queried)
Full report
- clearml
- Trust report
- zenml
- Trust report
Choose clearml if…
- Tags unique to clearml: ai, clearml, control, deeplearning.
- When you require a single platform for managing experiments, orchestrating pipelines, and serving models in your AI projects
- More GitHub stars (6.9k vs 5.6k) - visibility, not fit.
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
Choose zenml if…
- 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, data-science, genai.
- Also covers AI Agents, Developer Tools.
- 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 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
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (clearml/clearml) · observed Sep 27, 2026
- GitHub forks (clearml/clearml) · observed Sep 27, 2026
- Last push (clearml/clearml) · observed Sep 23, 2026
- License file (Apache-2.0) · observed Sep 27, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (zenml-io/zenml) · observed Sep 20, 2026
- GitHub forks (zenml-io/zenml) · observed Sep 20, 2026
- Last push (zenml-io/zenml) · observed Sep 18, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: clearml 6.9k · zenml 5.6k (synced Sep 27, 2026).
Common questions
- What is the difference between clearml and zenml?
- clearml: MLOps/LLMOps solution for CI/CD in AI workloads. zenml: One AI Platform from Pipelines to Agents. See the comparison table for live GitHub stats and shared categories.
- When should I choose clearml over zenml?
- Choose clearml over zenml when Tags unique to clearml: ai, clearml, control, deeplearning; When you require a single platform for managing experiments, orchestrating pipelines, and serving models in your AI projects; More GitHub stars (6.9k vs 5.6k) - visibility, not fit.
- When should I choose zenml over clearml?
- Choose zenml over clearml when 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, data-science, genai; Also covers AI Agents, Developer Tools; 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 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 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
- Is clearml or zenml more popular on GitHub?
- clearml has more GitHub stars (6,891 vs 5,582). Stars measure visibility, not whether either tool fits your constraints.
- Are clearml and zenml open source?
- Yes - both are open-source projects on GitHub (clearml: Apache-2.0, zenml: Apache-2.0).
- Where can I find alternatives to clearml or zenml?
- GraphCanon lists graph-backed alternatives at clearml alternatives and zenml alternatives (clearml markdown twin, zenml markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, clearml or zenml?
- clearml: Very active. zenml: 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 zenml?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: clearml trust report; zenml trust report.