Home/Compare/autoai vs ColossalAI

Comparison

autoai vs ColossalAI

Verdict

Pick autoai when tags unique to autoai: automl, ml, machine-learning, codegen; pick ColossalAI when tags unique to ColossalAI: big-model, heterogeneous-training, foundation models, data-parallelism.

Markdown twin · autoai alternatives · ColossalAI alternatives

GraphCanon updated today

autoai logo

autoai

blobcity/autoai

186pushed Mar 25, 2025
vs
ColossalAI logo

ColossalAI

hpcaitech/ColossalAI

41kpushed May 25, 2026

Trust & integrity

SignalautoaiColossalAI
Maintenance
Dormant (473d since push)
As of today · github_public_v1
Steady (46d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Organization account
As of today · github_public_v1
Security (OSV)
12 low (12 low)
As of today · osv@v1
No lockfile
As of today · none

Tagline

autoai
Python based framework for Automatic AI for Regression and Classification over numerical data. Performs model search, hyper-parameter tuning, and high-quality Jupyter Notebook code generation.
ColossalAI
Making large AI models cheaper, faster and more accessible

Stars

autoai
186
ColossalAI
41k

Forks

autoai
46
ColossalAI
4.5k

Open issues

autoai
9
ColossalAI
501

Language

autoai
Python
ColossalAI
Python

Adopt for

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

Persona

autoai
-
ColossalAI
-

Runtime

autoai
-
ColossalAI
-

License

autoai
Apache-2.0
ColossalAI
Apache-2.0

Last pushed

autoai
Mar 25, 2025
ColossalAI
May 25, 2026

Categories

autoai
Model Training, Inference & Serving
ColossalAI
Model Training, Inference & Serving

Trust and health

Maintenance

autoai
Dormant (18%)
ColossalAI
Steady (60%)

Days since push

autoai
473d
ColossalAI
46d

Open issues (now)

autoai
9
ColossalAI
501

Security scan

autoai
12 low (12 low)
ColossalAI
No lockfile

Full report

ColossalAI
Trust report

Shared compatibility

  • Python · autoai: Python runtime · ColossalAI: Python runtime

Choose autoai if…

  • Tags unique to autoai: automl, ml, machine-learning, codegen.
  • Leaner open-issue backlog (9).

When NOT to use autoai

  • Last GitHub push was 474 days ago (dormant maintenance, Mar 25, 2025). Validate activity before betting a new project on autoai.
  • Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
  • Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.

Choose ColossalAI if…

  • Tags unique to ColossalAI: big-model, heterogeneous-training, foundation models, data-parallelism.
  • You require handling extremely large AI models with massive context windows, such as over 2M tokens.
  • More GitHub stars (41k vs 186) - visibility, not fit.

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.

Explore

Sources

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

GitHub stars on cards: autoai 186 · ColossalAI 41k (synced Jul 11, 2026).

Common questions

What is the difference between autoai and ColossalAI?
autoai: Python based framework for Automatic AI for Regression and Classification over numerical data. Performs model search, hyper-parameter tuning, and high-quality Jupyter Notebook code generation.. ColossalAI: Making large AI models cheaper, faster and more accessible. See the comparison table for live GitHub stats and shared categories.
When should I choose autoai over ColossalAI?
Choose autoai over ColossalAI when Tags unique to autoai: automl, ml, machine-learning, codegen; Leaner open-issue backlog (9).
When should I choose ColossalAI over autoai?
Choose ColossalAI over autoai when Tags unique to ColossalAI: big-model, heterogeneous-training, foundation models, data-parallelism; You require handling extremely large AI models with massive context windows, such as over 2M tokens; More GitHub stars (41k vs 186) - visibility, not fit.
When should I avoid autoai?
Last GitHub push was 474 days ago (dormant maintenance, Mar 25, 2025). Validate activity before betting a new project on autoai. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
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.
Is autoai or ColossalAI more popular on GitHub?
ColossalAI has more GitHub stars (41,408 vs 186). Stars measure visibility, not whether either tool fits your constraints.
Are autoai and ColossalAI open source?
Yes - both are open-source projects on GitHub (autoai: Apache-2.0, ColossalAI: Apache-2.0).
Where can I find alternatives to autoai or ColossalAI?
GraphCanon lists graph-backed alternatives at autoai alternatives and ColossalAI alternatives (autoai markdown twin, ColossalAI 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, autoai or ColossalAI?
autoai: Dormant. ColossalAI: Steady. 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 autoai and ColossalAI?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: autoai trust report; ColossalAI trust report.