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Home/Compare/UER-py vs ColossalAI

Comparison

UER-py vs ColossalAI

Verdict

Pick UER-py when tags unique to UER-py: albert, bart, bert, chinese; pick ColossalAI when tags unique to ColossalAI: ai, big-model, data-parallelism, deep-learning.

Markdown twin · UER-py alternatives · ColossalAI alternatives

GraphCanon updated today

UER-py logo

UER-py

dbiir/UER-py

★ 3.1kpushed May 9, 2024
vs
ColossalAI logo

ColossalAI

hpcaitech/ColossalAI

★ 41kpushed May 25, 2026

Trust & integrity

SignalUER-pyColossalAI
Maintenance
Dormant (793d 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)
No lockfile
As of today · none
No lockfile
As of today · none
UER-py trust reportColossalAI trust reportTrust methodology

Tagline

UER-py
Open Source Pre-training Model Framework in PyTorch & Pre-trained Model Zoo
ColossalAI
Making large AI models cheaper, faster and more accessible

Stars

UER-py
3.1k
ColossalAI
41k

Forks

UER-py
520
ColossalAI
4.5k

Open issues

UER-py
136
ColossalAI
501

Language

UER-py
Python
ColossalAI
Python

Adopt for

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

Persona

UER-py
-
ColossalAI
-

Runtime

UER-py
-
ColossalAI
-

License

UER-py
Apache-2.0
ColossalAI
Apache-2.0

Last pushed

UER-py
May 9, 2024
ColossalAI
May 25, 2026

Categories

UER-py
Model Training
ColossalAI
Inference & Serving, Model Training

Trust and health

Maintenance

UER-py
Dormant (18%)
ColossalAI
Steady (60%)

Days since push

UER-py
793d
ColossalAI
46d

Open issues (now)

UER-py
136
ColossalAI
501

Full report

UER-py
Trust report
ColossalAI
Trust report

Choose UER-py if…

  • Tags unique to UER-py: albert, bart, bert, chinese.
  • Leaner open-issue backlog (136).

When NOT to use UER-py

  • Last GitHub push was 793 days ago (dormant maintenance, May 9, 2024). Validate activity before betting a new project on UER-py.
  • Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
GitHubDetails

Choose ColossalAI if…

  • 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

Explore

UER-py trust report →ColossalAI trust report →Model Training category →Inference & Serving 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: UER-py 3.1k · ColossalAI 41k (synced Jul 11, 2026).

Common questions

What is the difference between UER-py and ColossalAI?
UER-py: Open Source Pre-training Model Framework in PyTorch & Pre-trained Model Zoo. 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 UER-py over ColossalAI?
Choose UER-py over ColossalAI when Tags unique to UER-py: albert, bart, bert, chinese; Leaner open-issue backlog (136).
When should I choose ColossalAI over UER-py?
Choose ColossalAI over UER-py when 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 avoid UER-py?
Last GitHub push was 793 days ago (dormant maintenance, May 9, 2024). Validate activity before betting a new project on UER-py. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
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 UER-py or ColossalAI more popular on GitHub?
ColossalAI has more GitHub stars (41,408 vs 3,109). Stars measure visibility, not whether either tool fits your constraints.
Are UER-py and ColossalAI open source?
Yes - both are open-source projects on GitHub (UER-py: Apache-2.0, ColossalAI: Apache-2.0).
Where can I find alternatives to UER-py or ColossalAI?
GraphCanon lists graph-backed alternatives at UER-py alternatives and ColossalAI alternatives (UER-py 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, UER-py or ColossalAI?
UER-py: 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 UER-py and ColossalAI?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: UER-py trust report; ColossalAI trust report.