Home/Compare/ColossalAI vs fastDeploy

Comparison

ColossalAI vs fastDeploy

Verdict

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

Markdown twin · ColossalAI alternatives · fastDeploy alternatives

GraphCanon updated today

ColossalAI logo

ColossalAI

hpcaitech/ColossalAI

41kpushed Jul 13, 2026
vs
fastDeploy logo

fastDeploy

notAI-tech/fastDeploy

105pushed Feb 10, 2026

Trust & integrity

SignalColossalAIfastDeploy
Maintenance
Very active (0d since push)
As of 1d · github_public_v1
Slowing (154d 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
OSV dependency advisories
No lockfile (source not queried)
As of 4d · osv@v1
No lockfile (source not queried)
As of today · 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

ColossalAI
Making large AI models cheaper, faster and more accessible
fastDeploy
Deploy DL/ ML inference pipelines with minimal extra code.

Stars

ColossalAI
41k
fastDeploy
105

Forks

ColossalAI
4.5k
fastDeploy
17

Open issues

ColossalAI
499
fastDeploy
0

Language

ColossalAI
Python
fastDeploy
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.
fastDeploy
-

Persona

ColossalAI
-
fastDeploy
-

Runtime

ColossalAI
-
fastDeploy
-

License

ColossalAI
Apache-2.0
fastDeploy
MIT

Last pushed

ColossalAI
Jul 13, 2026
fastDeploy
Feb 10, 2026

Categories

ColossalAI
Inference & Serving, Model Training
fastDeploy
Inference & Serving, Model Training, Speech & Audio

Trust and health

Maintenance

ColossalAI
Very active (96%)
fastDeploy
Slowing (36%)

Days since push

ColossalAI
0d
fastDeploy
154d

Open issues (now)

ColossalAI
499
fastDeploy
0

Full report

ColossalAI
Trust report
fastDeploy
Trust report

Choose ColossalAI if…

  • License: ColossalAI is Apache-2.0, fastDeploy is MIT.
  • Tags unique to ColossalAI: ai, big model, data-parallelism, distributed-computing.
  • 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.

Choose fastDeploy if…

  • License: fastDeploy is MIT, ColossalAI is Apache-2.0.
  • Tags unique to fastDeploy: docker, falcon, gevent, gunicorn.
  • Also covers Speech & Audio.

When NOT to use fastDeploy

  • Last GitHub push was 155 days ago (slowing maintenance, Feb 10, 2026). Validate activity before betting a new project on fastDeploy.
  • Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
  • Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.

Explore

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 · fastDeploy 105 (synced Jul 14, 2026).

Common questions

What is the difference between ColossalAI and fastDeploy?
ColossalAI: Making large AI models cheaper, faster and more accessible. fastDeploy: Deploy DL/ ML inference pipelines with minimal extra code.. See the comparison table for live GitHub stats and shared categories.
When should I choose ColossalAI over fastDeploy?
Choose ColossalAI over fastDeploy when License: ColossalAI is Apache-2.0, fastDeploy is MIT; Tags unique to ColossalAI: ai, big model, data-parallelism, distributed-computing; You require handling extremely large AI models with massive context windows, such as over 2M tokens.
When should I choose fastDeploy over ColossalAI?
Choose fastDeploy over ColossalAI when License: fastDeploy is MIT, ColossalAI is Apache-2.0; Tags unique to fastDeploy: docker, falcon, gevent, gunicorn; Also covers Speech & Audio.
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 fastDeploy?
Last GitHub push was 155 days ago (slowing maintenance, Feb 10, 2026). Validate activity before betting a new project on fastDeploy. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
Is ColossalAI or fastDeploy more popular on GitHub?
ColossalAI has more GitHub stars (41,413 vs 105). Stars measure visibility, not whether either tool fits your constraints.
Are ColossalAI and fastDeploy open source?
Yes - both are open-source projects on GitHub (ColossalAI: Apache-2.0, fastDeploy: MIT).
Where can I find alternatives to ColossalAI or fastDeploy?
GraphCanon lists graph-backed alternatives at ColossalAI alternatives and fastDeploy alternatives (ColossalAI markdown twin, fastDeploy 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 fastDeploy?
ColossalAI: Very active. fastDeploy: Slowing. 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 fastDeploy?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ColossalAI trust report; fastDeploy trust report.

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