Comparison
clearml vs pai
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 pai if pai is an open-source solution focused on resource scheduling and cluster management that supports deep learning frameworks including TensorFlow, PyTorch, and Chainer.
Markdown twin · clearml alternatives · pai alternatives
GraphCanon updated Sep 29, 2026
16views this month
Trust & integrity
| Signal | clearml | pai |
|---|---|---|
| Maintenance | Very active (3d since push) As of Sep 27, 2026 · github_public_v1 | Active (11d since push) As of Sep 29, 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 29, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 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
- pai
- Resource scheduling and cluster management for AI
Stars
- clearml
- 6.9k
- pai
- 2.7k
Forks
- clearml
- 802
- pai
- 554
Open issues
- clearml
- 526
- pai
- 260
Language
- clearml
- Python
- pai
- JavaScript
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.
- pai
- pai is an open-source solution focused on resource scheduling and cluster management that supports deep learning frameworks including TensorFlow, PyTorch, and Chainer.
Persona
- clearml
- -
- pai
- -
Runtime
- clearml
- -
- pai
- -
License
- clearml
- Apache-2.0
- pai
- MIT
Last pushed
- clearml
- Sep 23, 2026
- pai
- Sep 18, 2026
Categories
- clearml
- Inference & Serving, Model Training
- pai
- Inference & Serving, Model Training
Trust and health
Maintenance
- clearml
- Very active (96%)
- pai
- Active (82%)
Days since push
- clearml
- 3d
- pai
- 11d
Open issues (now)
- clearml
- 526
- pai
- 260
Stars delta
- clearml
- +86 (30d)
- pai
- +8 (30d)
Open issues delta
- clearml
- -47 (30d)
- pai
- -22 (30d)
OSV dependency advisories
- clearml
- Published findings
- pai
- No lockfile (source not queried)
Full report
- clearml
- Trust report
- pai
- Trust report
Choose clearml if…
- clearml is primarily Python; pai is JavaScript.
- License: clearml is Apache-2.0, pai is MIT.
- Tags unique to clearml: clearml, control, deep-learning, 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 pai if…
- pai is primarily JavaScript; clearml is Python.
- License: pai is MIT, clearml is Apache-2.0.
- Tags unique to pai: artificial-intelligence, gpu, kubernetes, machine-learning.
- When you are working with JavaScript-based projects and need to integrate model training or serving operations within your tech stack seamlessly
When NOT to use pai
- For organizations that prefer a more comprehensive suite tailored for specific languages other than JavaScript, as the tool's focus is clearly on this language environment
- When looking for solutions strictly hosted in cloud environments, as pai also supports deployment in on-premise settings which could complicate decisions if cloud dependency is critical
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 (microsoft/pai) · observed Sep 29, 2026
- GitHub forks (microsoft/pai) · observed Sep 29, 2026
- Last push (microsoft/pai) · observed Sep 18, 2026
- License file (MIT) · observed Sep 29, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: clearml 6.9k · pai 2.7k (synced Sep 27, 2026).
Common questions
- What is the difference between clearml and pai?
- clearml: MLOps/LLMOps solution for CI/CD in AI workloads. pai: Resource scheduling and cluster management for AI. See the comparison table for live GitHub stats and shared categories.
- When should I choose clearml over pai?
- Choose clearml over pai when clearml is primarily Python; pai is JavaScript; License: clearml is Apache-2.0, pai is MIT; Tags unique to clearml: clearml, control, deep-learning, deeplearning; When you require a single platform for managing experiments, orchestrating pipelines, and serving models in your AI projects.
- When should I choose pai over clearml?
- Choose pai over clearml when pai is primarily JavaScript; clearml is Python; License: pai is MIT, clearml is Apache-2.0; Tags unique to pai: artificial-intelligence, gpu, kubernetes, machine-learning; When you are working with JavaScript-based projects and need to integrate model training or serving operations within your tech stack seamlessly.
- 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 pai?
- For organizations that prefer a more comprehensive suite tailored for specific languages other than JavaScript, as the tool's focus is clearly on this language environment When looking for solutions strictly hosted in cloud environments, as pai also supports deployment in on-premise settings which could complicate decisions if cloud dependency is critical
- Is clearml or pai more popular on GitHub?
- clearml has more GitHub stars (6,891 vs 2,694). Stars measure visibility, not whether either tool fits your constraints.
- Are clearml and pai open source?
- Yes - both are open-source projects on GitHub (clearml: Apache-2.0, pai: MIT).
- Where can I find alternatives to clearml or pai?
- GraphCanon lists graph-backed alternatives at clearml alternatives and pai alternatives (clearml markdown twin, pai 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 pai?
- clearml: Very active. pai: 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 pai?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: clearml trust report; pai trust report.