Comparison
ColossalAI vs whisper-timestamped
Verdict
Pick ColossalAI when license: ColossalAI is Apache-2.0, whisper-timestamped is AGPL-3.0; pick whisper-timestamped when license: whisper-timestamped is AGPL-3.0, ColossalAI is Apache-2.0.
Markdown twin · ColossalAI alternatives · whisper-timestamped alternatives
GraphCanon updated today
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Trust & integrity
| Signal | ColossalAI | whisper-timestamped |
|---|---|---|
| Maintenance | Steady (46d since push) As of today · github_public_v1 | Slowing (305d 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 criticals As of today · osv@v1 |
Tagline
- ColossalAI
- Making large AI models cheaper, faster and more accessible
- whisper-timestamped
- Multilingual Automatic Speech Recognition with word-level timestamps and confidence
Stars
- ColossalAI
- 41k
- whisper-timestamped
- 2.8k
Forks
- ColossalAI
- 4.5k
- whisper-timestamped
- 210
Open issues
- ColossalAI
- 501
- whisper-timestamped
- 49
Language
- ColossalAI
- Python
- whisper-timestamped
- 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.
- whisper-timestamped
- -
Persona
- ColossalAI
- -
- whisper-timestamped
- -
Runtime
- ColossalAI
- -
- whisper-timestamped
- -
License
- ColossalAI
- Apache-2.0
- whisper-timestamped
- AGPL-3.0
Last pushed
- ColossalAI
- May 25, 2026
- whisper-timestamped
- Sep 9, 2025
Categories
- ColossalAI
- Model Training, Inference & Serving
- whisper-timestamped
- Model Training, Inference & Serving, Speech & Audio
Trust and health
Maintenance
- ColossalAI
- Steady (60%)
- whisper-timestamped
- Slowing (36%)
Days since push
- ColossalAI
- 46d
- whisper-timestamped
- 305d
Open issues (now)
- ColossalAI
- 501
- whisper-timestamped
- 49
Security scan
- ColossalAI
- No lockfile
- whisper-timestamped
- No criticals
Full report
- ColossalAI
- Trust report
- whisper-timestamped
- Trust report
Shared compatibility
- Python · ColossalAI: Python runtime · whisper-timestamped: Python runtime
Choose ColossalAI if…
- License: ColossalAI is Apache-2.0, whisper-timestamped is AGPL-3.0.
- Tags unique to ColossalAI: ai, big-model, heterogeneous-training, foundation models.
- 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 whisper-timestamped if…
- License: whisper-timestamped is AGPL-3.0, ColossalAI is Apache-2.0.
- Tags unique to whisper-timestamped: asr, attention-seq2seq, attention-model, attention-mechanism.
- Also covers Speech & Audio.
- whisper-timestamped ships Docker support for self-hosted deployment.
When NOT to use whisper-timestamped
- Last GitHub push was 306 days ago (slowing maintenance, Sep 9, 2025). Validate activity before betting a new project on whisper-timestamped.
- 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.
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 (linto-ai/whisper-timestamped) · observed Jul 11, 2026
- GitHub forks (linto-ai/whisper-timestamped) · observed Jul 11, 2026
- Last push (linto-ai/whisper-timestamped) · observed Sep 9, 2025
- License file (AGPL-3.0) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: ColossalAI 41k · whisper-timestamped 2.8k (synced Jul 11, 2026).
Common questions
- What is the difference between ColossalAI and whisper-timestamped?
- ColossalAI: Making large AI models cheaper, faster and more accessible. whisper-timestamped: Multilingual Automatic Speech Recognition with word-level timestamps and confidence. See the comparison table for live GitHub stats and shared categories.
- When should I choose ColossalAI over whisper-timestamped?
- Choose ColossalAI over whisper-timestamped when License: ColossalAI is Apache-2.0, whisper-timestamped is AGPL-3.0; Tags unique to ColossalAI: ai, big-model, heterogeneous-training, foundation models; You require handling extremely large AI models with massive context windows, such as over 2M tokens.
- When should I choose whisper-timestamped over ColossalAI?
- Choose whisper-timestamped over ColossalAI when License: whisper-timestamped is AGPL-3.0, ColossalAI is Apache-2.0; Tags unique to whisper-timestamped: asr, attention-seq2seq, attention-model, attention-mechanism; Also covers Speech & Audio; whisper-timestamped ships Docker support for self-hosted deployment.
- 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 whisper-timestamped?
- Last GitHub push was 306 days ago (slowing maintenance, Sep 9, 2025). Validate activity before betting a new project on whisper-timestamped. 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.
- Is ColossalAI or whisper-timestamped more popular on GitHub?
- ColossalAI has more GitHub stars (41,408 vs 2,823). Stars measure visibility, not whether either tool fits your constraints.
- Are ColossalAI and whisper-timestamped open source?
- Yes - both are open-source projects on GitHub (ColossalAI: Apache-2.0, whisper-timestamped: AGPL-3.0).
- Where can I find alternatives to ColossalAI or whisper-timestamped?
- GraphCanon lists graph-backed alternatives at ColossalAI alternatives and whisper-timestamped alternatives (ColossalAI markdown twin, whisper-timestamped 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 whisper-timestamped?
- ColossalAI: Steady. whisper-timestamped: 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 whisper-timestamped?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ColossalAI trust report; whisper-timestamped trust report.