Comparison
ColossalAI vs automl-gs
Verdict
Pick ColossalAI when license: ColossalAI is Apache-2.0, automl-gs is MIT; pick automl-gs when license: automl-gs is MIT, ColossalAI is Apache-2.0.
Markdown twin · ColossalAI alternatives · automl-gs alternatives
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Trust & integrity
| Signal | ColossalAI | automl-gs |
|---|---|---|
| Maintenance | Steady (46d since push) As of 1d · github_public_v1 | Dormant (2454d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of 1d · github_public_v1 | Not a fork · Personal account As of today · github_public_v1 |
| Security (OSV) | No lockfile As of 1d · none | 2 high, 5 medium, 7 low (2 high, 5 medium, 7 low) As of today · osv@v1 |
Tagline
- ColossalAI
- Making large AI models cheaper, faster and more accessible
- automl-gs
- Provide an input CSV and a target field to predict, generate a model + code to run it.
Stars
- ColossalAI
- 41k
- automl-gs
- 1.9k
Forks
- ColossalAI
- 4.5k
- automl-gs
- 181
Open issues
- ColossalAI
- 501
- automl-gs
- 28
Language
- ColossalAI
- Python
- automl-gs
- 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.
- automl-gs
- -
Persona
- ColossalAI
- -
- automl-gs
- -
Runtime
- ColossalAI
- -
- automl-gs
- -
License
- ColossalAI
- Apache-2.0
- automl-gs
- MIT
Last pushed
- ColossalAI
- May 25, 2026
- automl-gs
- Oct 22, 2019
Categories
- ColossalAI
- Inference & Serving, Model Training
- automl-gs
- Model Training
Trust and health
Maintenance
- ColossalAI
- Steady (60%)
- automl-gs
- Dormant (18%)
Days since push
- ColossalAI
- 46d
- automl-gs
- 2454d
Open issues (now)
- ColossalAI
- 501
- automl-gs
- 28
Owner type
- ColossalAI
- Organization
- automl-gs
- User
Security scan
- ColossalAI
- No lockfile
- automl-gs
- 2 high, 5 medium, 7 low (2 high, 5 medium, 7 low)
Full report
- ColossalAI
- Trust report
- automl-gs
- Trust report
Choose ColossalAI if…
- License: ColossalAI is Apache-2.0, automl-gs 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.
Choose automl-gs if…
- License: automl-gs is MIT, ColossalAI is Apache-2.0.
- Tags unique to automl-gs: automl, keras, machine-learning, python.
- Leaner open-issue backlog (28).
When NOT to use automl-gs
- Last GitHub push was 2454 days ago (dormant maintenance, Oct 22, 2019). Validate activity before betting a new project on automl-gs.
- 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 (hpcaitech/ColossalAI) · observed Jul 11, 2026
- GitHub forks (hpcaitech/ColossalAI) · observed Jul 11, 2026
- Last push (hpcaitech/ColossalAI) · observed May 25, 2026
- License file (Apache-2.0) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (minimaxir/automl-gs) · observed Jul 11, 2026
- GitHub forks (minimaxir/automl-gs) · observed Jul 11, 2026
- Last push (minimaxir/automl-gs) · observed Oct 22, 2019
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: ColossalAI 41k · automl-gs 1.9k (synced Jul 11, 2026).
Common questions
- What is the difference between ColossalAI and automl-gs?
- ColossalAI: Making large AI models cheaper, faster and more accessible. automl-gs: Provide an input CSV and a target field to predict, generate a model + code to run it.. See the comparison table for live GitHub stats and shared categories.
- When should I choose ColossalAI over automl-gs?
- Choose ColossalAI over automl-gs when License: ColossalAI is Apache-2.0, automl-gs 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 automl-gs over ColossalAI?
- Choose automl-gs over ColossalAI when License: automl-gs is MIT, ColossalAI is Apache-2.0; Tags unique to automl-gs: automl, keras, machine-learning, python; Leaner open-issue backlog (28).
- 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 automl-gs?
- Last GitHub push was 2454 days ago (dormant maintenance, Oct 22, 2019). Validate activity before betting a new project on automl-gs. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- Is ColossalAI or automl-gs more popular on GitHub?
- ColossalAI has more GitHub stars (41,408 vs 1,866). Stars measure visibility, not whether either tool fits your constraints.
- Are ColossalAI and automl-gs open source?
- Yes - both are open-source projects on GitHub (ColossalAI: Apache-2.0, automl-gs: MIT).
- Where can I find alternatives to ColossalAI or automl-gs?
- GraphCanon lists graph-backed alternatives at ColossalAI alternatives and automl-gs alternatives (ColossalAI markdown twin, automl-gs 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 automl-gs?
- ColossalAI: Steady. automl-gs: Dormant. 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 automl-gs?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ColossalAI trust report; automl-gs trust report.