Home/Compare/FATE vs ColossalAI

Comparison

FATE vs ColossalAI

Verdict

Pick FATE when tags unique to FATE: fate, algorithm, machine-learning, python; pick ColossalAI when tags unique to ColossalAI: deep-learning, ai, big-model, heterogeneous-training.

Markdown twin · FATE alternatives · ColossalAI alternatives

GraphCanon updated today

FATE logo

FATE

FederatedAI/FATE

6.1kpushed Nov 19, 2024
vs
ColossalAI logo

ColossalAI

hpcaitech/ColossalAI

41kpushed May 25, 2026

Trust & integrity

SignalFATEColossalAI
Maintenance
Dormant (599d 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

Tagline

FATE
An Industrial Grade Federated Learning Framework
ColossalAI
Making large AI models cheaper, faster and more accessible

Stars

FATE
6.1k
ColossalAI
41k

Forks

FATE
1.6k
ColossalAI
4.5k

Open issues

FATE
21
ColossalAI
501

Language

FATE
Python
ColossalAI
Python

Adopt for

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

Persona

FATE
-
ColossalAI
-

Runtime

FATE
-
ColossalAI
-

License

FATE
Apache-2.0
ColossalAI
Apache-2.0

Last pushed

FATE
Nov 19, 2024
ColossalAI
May 25, 2026

Categories

FATE
Model Training, Computer Vision, Inference & Serving
ColossalAI
Model Training, Inference & Serving

Trust and health

Maintenance

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

Days since push

FATE
599d
ColossalAI
46d

Open issues (now)

FATE
21
ColossalAI
501

Full report

ColossalAI
Trust report

Choose FATE if…

  • Tags unique to FATE: fate, algorithm, machine-learning, python.
  • Also covers Computer Vision.
  • Leaner open-issue backlog (21).

When NOT to use FATE

  • Last GitHub push was 599 days ago (dormant maintenance, Nov 19, 2024). Validate activity before betting a new project on FATE.
  • 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: deep-learning, ai, big-model, heterogeneous-training.
  • You require handling extremely large AI models with massive context windows, such as over 2M tokens.
  • More GitHub stars (41k vs 6.1k) - 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: FATE 6.1k · ColossalAI 41k (synced Jul 11, 2026).

Common questions

What is the difference between FATE and ColossalAI?
FATE: An Industrial Grade Federated Learning Framework. 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 FATE over ColossalAI?
Choose FATE over ColossalAI when Tags unique to FATE: fate, algorithm, machine-learning, python; Also covers Computer Vision; Leaner open-issue backlog (21).
When should I choose ColossalAI over FATE?
Choose ColossalAI over FATE when Tags unique to ColossalAI: deep-learning, ai, big-model, heterogeneous-training; You require handling extremely large AI models with massive context windows, such as over 2M tokens; More GitHub stars (41k vs 6.1k) - visibility, not fit.
When should I avoid FATE?
Last GitHub push was 599 days ago (dormant maintenance, Nov 19, 2024). Validate activity before betting a new project on FATE. 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 FATE or ColossalAI more popular on GitHub?
ColossalAI has more GitHub stars (41,408 vs 6,084). Stars measure visibility, not whether either tool fits your constraints.
Are FATE and ColossalAI open source?
Yes - both are open-source projects on GitHub (FATE: Apache-2.0, ColossalAI: Apache-2.0).
Where can I find alternatives to FATE or ColossalAI?
GraphCanon lists graph-backed alternatives at FATE alternatives and ColossalAI alternatives (FATE 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, FATE or ColossalAI?
FATE: 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 FATE and ColossalAI?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: FATE trust report; ColossalAI trust report.