Comparison
ColossalAI vs RLTF
Verdict
Pick ColossalAI when license: ColossalAI is Apache-2.0, RLTF is BSD-3-Clause; pick RLTF when license: RLTF is BSD-3-Clause, ColossalAI is Apache-2.0.
Markdown twin · ColossalAI alternatives · RLTF alternatives
GraphCanon updated today
Trust & integrity
| Signal | ColossalAI | RLTF |
|---|---|---|
| Maintenance | Steady (46d since push) As of today · github_public_v1 | Dormant (644d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Personal account As of today · github_public_v1 |
| Security (OSV) | No lockfile As of today · none | 75 low (75 low) As of today · osv@v1 |
Tagline
- ColossalAI
- Making large AI models cheaper, faster and more accessible
- RLTF
- Accepted by Transactions on Machine Learning Research (TMLR)
Stars
- ColossalAI
- 41k
- RLTF
- 135
Forks
- ColossalAI
- 4.5k
- RLTF
- 7
Open issues
- ColossalAI
- 501
- RLTF
- 0
Language
- ColossalAI
- Python
- RLTF
- 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.
- RLTF
- -
Persona
- ColossalAI
- -
- RLTF
- -
Runtime
- ColossalAI
- -
- RLTF
- -
License
- ColossalAI
- Apache-2.0
- RLTF
- BSD-3-Clause
Last pushed
- ColossalAI
- May 25, 2026
- RLTF
- Oct 5, 2024
Categories
- ColossalAI
- Model Training, Inference & Serving
- RLTF
- Model Training
Trust and health
Maintenance
- ColossalAI
- Steady (60%)
- RLTF
- Dormant (18%)
Days since push
- ColossalAI
- 46d
- RLTF
- 644d
Open issues (now)
- ColossalAI
- 501
- RLTF
- 0
Owner type
- ColossalAI
- Organization
- RLTF
- User
Security scan
- ColossalAI
- No lockfile
- RLTF
- 75 low (75 low)
Full report
- ColossalAI
- Trust report
- RLTF
- Trust report
Shared compatibility
- Python · ColossalAI: Python runtime · RLTF: Python runtime
Choose ColossalAI if…
- License: ColossalAI is Apache-2.0, RLTF is BSD-3-Clause.
- Tags unique to ColossalAI: deep-learning, ai, big-model, heterogeneous-training.
- 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 RLTF if…
- License: RLTF is BSD-3-Clause, ColossalAI is Apache-2.0.
- Tags unique to RLTF: python.
- Leaner open-issue backlog (0).
When NOT to use RLTF
- Last GitHub push was 644 days ago (dormant maintenance, Oct 5, 2024). Validate activity before betting a new project on RLTF.
- 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 (Zyq-scut/RLTF) · observed Jul 11, 2026
- GitHub forks (Zyq-scut/RLTF) · observed Jul 11, 2026
- Last push (Zyq-scut/RLTF) · observed Oct 5, 2024
- License file (BSD-3-Clause) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: ColossalAI 41k · RLTF 135 (synced Jul 11, 2026).
Common questions
- What is the difference between ColossalAI and RLTF?
- ColossalAI: Making large AI models cheaper, faster and more accessible. RLTF: Accepted by Transactions on Machine Learning Research (TMLR). See the comparison table for live GitHub stats and shared categories.
- When should I choose ColossalAI over RLTF?
- Choose ColossalAI over RLTF when License: ColossalAI is Apache-2.0, RLTF is BSD-3-Clause; Tags unique to ColossalAI: deep-learning, ai, big-model, heterogeneous-training; Also covers Inference & Serving; You require handling extremely large AI models with massive context windows, such as over 2M tokens.
- When should I choose RLTF over ColossalAI?
- Choose RLTF over ColossalAI when License: RLTF is BSD-3-Clause, ColossalAI is Apache-2.0; Tags unique to RLTF: python; Leaner open-issue backlog (0).
- 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 RLTF?
- Last GitHub push was 644 days ago (dormant maintenance, Oct 5, 2024). Validate activity before betting a new project on RLTF. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- Is ColossalAI or RLTF more popular on GitHub?
- ColossalAI has more GitHub stars (41,408 vs 135). Stars measure visibility, not whether either tool fits your constraints.
- Are ColossalAI and RLTF open source?
- Yes - both are open-source projects on GitHub (ColossalAI: Apache-2.0, RLTF: BSD-3-Clause).
- Where can I find alternatives to ColossalAI or RLTF?
- GraphCanon lists graph-backed alternatives at ColossalAI alternatives and RLTF alternatives (ColossalAI markdown twin, RLTF 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 RLTF?
- ColossalAI: Steady. RLTF: 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 RLTF?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ColossalAI trust report; RLTF trust report.