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Comparison

ColossalAI vs optuna

Verdict

Pick ColossalAI when license: ColossalAI is Apache-2.0, optuna is MIT; pick optuna when license: optuna is MIT, ColossalAI is Apache-2.0.

Markdown twin · ColossalAI alternatives · optuna alternatives

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ColossalAI logo

ColossalAI

hpcaitech/ColossalAI

★ 41kpushed May 25, 2026
vs
optuna logo

optuna

optuna/optuna

★ 14kpushed Jul 10, 2026

Trust & integrity

SignalColossalAIoptuna
Maintenance
Steady (46d since push)
As of 1d · github_public_v1
Very active (1d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of 1d · github_public_v1
Not a fork · Organization account
As of today · github_public_v1
Security (OSV)
No lockfile
As of 1d · none
No lockfile
As of today · none
ColossalAI trust reportoptuna trust reportTrust methodology

Tagline

ColossalAI
Making large AI models cheaper, faster and more accessible
optuna
A hyperparameter optimization framework

Stars

ColossalAI
41k
optuna
14k

Forks

ColossalAI
4.5k
optuna
1.4k

Open issues

ColossalAI
501
optuna
23

Language

ColossalAI
Python
optuna
Python

Adopt for

ColossalAI
ColossalAI is a Python library that leverages advanced parallelism techniques for more efficient and cost-effective development of large-scale AI models.
optuna
-

Persona

ColossalAI
-
optuna
-

Runtime

ColossalAI
-
optuna
-

License

ColossalAI
Apache-2.0
optuna
MIT

Last pushed

ColossalAI
May 25, 2026
optuna
Jul 10, 2026

Categories

ColossalAI
Inference & Serving, Model Training
optuna
Model Training

Trust and health

Maintenance

ColossalAI
Steady (60%)
optuna
Very active (96%)

Days since push

ColossalAI
46d
optuna
1d

Open issues (now)

ColossalAI
501
optuna
23

Full report

ColossalAI
Trust report
optuna
Trust report

Shared compatibility

  • Python · ColossalAI: Python runtime · optuna: Python runtime

Choose ColossalAI if…

  • License: ColossalAI is Apache-2.0, optuna is MIT.
  • Tags unique to ColossalAI: ai, big model, data-parallelism, deep-learning.
  • Also covers Inference & Serving.
  • You require handling extremely large AI models with massive context windows, such as over 2M tokens.

When NOT to use ColossalAI

  • You are working in an environment that does not support Linux OS, as ColossalAI currently offers no support for other operating systems.
  • Your current CUDA version is less than 11.0 or your GPU compute capability is below 7.0 (pre-V100/RTX20 series).
  • You cannot satisfy the minimum hardware and software requirements specified, such as PyTorch >= 2.2 and Python >= 3.7.
GitHubDetails

Choose optuna if…

  • License: optuna is MIT, ColossalAI is Apache-2.0.
  • Tags unique to optuna: distributed, hyperparameter-optimization, machine-learning, parallel.
  • More recently updated (last pushed Jul 10, 2026).

When NOT to use optuna

  • Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
GitHubDetails

Explore

ColossalAI trust report →optuna trust report →Inference & Serving category →Model Training category →All comparisonsStack workflowsTrending tools

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: ColossalAI 41k · optuna 14k (synced Jul 11, 2026).

Common questions

What is the difference between ColossalAI and optuna?
ColossalAI: Making large AI models cheaper, faster and more accessible. optuna: A hyperparameter optimization framework. See the comparison table for live GitHub stats and shared categories.
When should I choose ColossalAI over optuna?
Choose ColossalAI over optuna when License: ColossalAI is Apache-2.0, optuna is MIT; Tags unique to ColossalAI: ai, big model, data-parallelism, deep-learning; Also covers Inference & Serving; You require handling extremely large AI models with massive context windows, such as over 2M tokens.
When should I choose optuna over ColossalAI?
Choose optuna over ColossalAI when License: optuna is MIT, ColossalAI is Apache-2.0; Tags unique to optuna: distributed, hyperparameter-optimization, machine-learning, parallel; More recently updated (last pushed Jul 10, 2026).
When should I avoid ColossalAI?
You are working in an environment that does not support Linux OS, as ColossalAI currently offers no support for other operating systems. Your current CUDA version is less than 11.0 or your GPU compute capability is below 7.0 (pre-V100/RTX20 series). You cannot satisfy the minimum hardware and software requirements specified, such as PyTorch >= 2.2 and Python >= 3.7.
When should I avoid optuna?
Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
Is ColossalAI or optuna more popular on GitHub?
ColossalAI has more GitHub stars (41,408 vs 14,482). Stars measure visibility, not whether either tool fits your constraints.
Are ColossalAI and optuna open source?
Yes - both are open-source projects on GitHub (ColossalAI: Apache-2.0, optuna: MIT).
Where can I find alternatives to ColossalAI or optuna?
GraphCanon lists graph-backed alternatives at ColossalAI alternatives and optuna alternatives (ColossalAI markdown twin, optuna 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, ColossalAI or optuna?
ColossalAI: Steady. optuna: 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 ColossalAI and optuna?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ColossalAI trust report; optuna trust report.