Comparison
clearml vs Made-With-ML
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 Made-With-ML if made-With-ML is about equipping developers with practical resources to design, develop, deploy and iterate on production-grade machine learning applications within their software engineering workflows.
Markdown twin · clearml alternatives · Made-With-ML alternatives
GraphCanon updated 1w
vs
Trust & integrity
| Signal | clearml | Made-With-ML |
|---|---|---|
| Maintenance | Active (7d since push) As of 2w · github_public_v1 | Slowing (162d since push) As of 1w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Personal account As of 1w · github_public_v1 |
| OSV dependency advisories | Published findings As of 1mo · osv@v1 | Published findings As of 1mo · 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
- Made-With-ML
- Learn to develop, deploy and iterate on production-grade ML applications
Stars
- clearml
- 6.8k
- Made-With-ML
- 49k
Forks
- clearml
- 785
- Made-With-ML
- 7.7k
Open issues
- clearml
- 573
- Made-With-ML
- 26
Language
- clearml
- Python
- Made-With-ML
- Jupyter Notebook
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.
- Made-With-ML
- Made-With-ML is about equipping developers with practical resources to design, develop, deploy and iterate on production-grade machine learning applications within their software engineering workflows.
Persona
- clearml
- -
- Made-With-ML
- -
Runtime
- clearml
- -
- Made-With-ML
- -
License
- clearml
- Apache-2.0
- Made-With-ML
- MIT
Last pushed
- clearml
- Jul 27, 2026
- Made-With-ML
- Mar 4, 2026
Categories
- clearml
- Inference & Serving, Model Training
- Made-With-ML
- Developer Tools, Inference & Serving, Model Training
Trust and health
Maintenance
- clearml
- Active (82%)
- Made-With-ML
- Slowing (36%)
Days since push
- clearml
- 7d
- Made-With-ML
- 162d
Open issues (now)
- clearml
- 573
- Made-With-ML
- 26
Stars delta
- clearml
- Unknown
- Made-With-ML
- +371 (30d)
Open issues delta
- clearml
- Unknown
- Made-With-ML
- -1 (30d)
Owner type
- clearml
- Organization
- Made-With-ML
- User
Full report
- clearml
- Trust report
- Made-With-ML
- Trust report
Choose clearml if…
- clearml is primarily Python; Made-With-ML is Jupyter Notebook.
- License: clearml is Apache-2.0, Made-With-ML is MIT.
- 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
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 Made-With-ML if…
- Made-With-ML is primarily Jupyter Notebook; clearml is Python.
- License: Made-With-ML is MIT, clearml is Apache-2.0.
- Requirements: A foundational understanding of Python programming is required to fully benefit from the learning resources provided..
- Tags unique to Made-With-ML: data-engineering, data-quality, data-science, distributed-ml.
- Also covers Developer Tools.
- If you are looking for comprehensive tutorials that connect foundational ML concepts directly with hands-on coding practices using Python and PyTorch.
When NOT to use Made-With-ML
- If you are looking for a niche-focused tool that caters specifically to a particular machine learning framework other than PyTorch.
- For developers who already have strong backgrounds in MLOps and require highly specialized tools for managing production-grade ML deployments without additional educational support.
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 Aug 3, 2026
- GitHub forks (clearml/clearml) · observed Aug 3, 2026
- Last push (clearml/clearml) · observed Jul 27, 2026
- License file (Apache-2.0) · observed Aug 3, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (GokuMohandas/Made-With-ML) · observed Aug 14, 2026
- GitHub forks (GokuMohandas/Made-With-ML) · observed Aug 14, 2026
- Last push (GokuMohandas/Made-With-ML) · observed Mar 4, 2026
- License file (MIT) · observed Aug 14, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: clearml 6.8k · Made-With-ML 49k (synced Aug 3, 2026).
Common questions
- What is the difference between clearml and Made-With-ML?
- clearml: MLOps/LLMOps solution for CI/CD in AI workloads. Made-With-ML: Learn to develop, deploy and iterate on production-grade ML applications. See the comparison table for live GitHub stats and shared categories.
- When should I choose clearml over Made-With-ML?
- Choose clearml over Made-With-ML when clearml is primarily Python; Made-With-ML is Jupyter Notebook; License: clearml is Apache-2.0, Made-With-ML is MIT; 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.
- When should I choose Made-With-ML over clearml?
- Choose Made-With-ML over clearml when Made-With-ML is primarily Jupyter Notebook; clearml is Python; License: Made-With-ML is MIT, clearml is Apache-2.0; Requirements: A foundational understanding of Python programming is required to fully benefit from the learning resources provided.; Tags unique to Made-With-ML: data-engineering, data-quality, data-science, distributed-ml; Also covers Developer Tools; If you are looking for comprehensive tutorials that connect foundational ML concepts directly with hands-on coding practices using Python and PyTorch.
- 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 Made-With-ML?
- If you are looking for a niche-focused tool that caters specifically to a particular machine learning framework other than PyTorch. For developers who already have strong backgrounds in MLOps and require highly specialized tools for managing production-grade ML deployments without additional educational support.
- Is clearml or Made-With-ML more popular on GitHub?
- Made-With-ML has more GitHub stars (49,074 vs 6,805). Stars measure visibility, not whether either tool fits your constraints.
- Are clearml and Made-With-ML open source?
- Yes - both are open-source projects on GitHub (clearml: Apache-2.0, Made-With-ML: MIT).
- Where can I find alternatives to clearml or Made-With-ML?
- GraphCanon lists graph-backed alternatives at clearml alternatives and Made-With-ML alternatives (clearml markdown twin, Made-With-ML 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 Made-With-ML?
- clearml: Active. Made-With-ML: 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 clearml and Made-With-ML?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: clearml trust report; Made-With-ML trust report.