--- title: "ColossalAI vs whisper-timestamped" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hpcaitech-colossalai-vs-linto-ai-whisper-timestamped" tools: ["hpcaitech-colossalai", "linto-ai-whisper-timestamped"] --- # ColossalAI vs whisper-timestamped *GraphCanon updated Jul 11, 2026* ## 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. [ColossalAI](https://www.colossalai.org) reports 41k GitHub stars, 4.5k forks, and 501 open issues, last pushed May 25, 2026. [whisper-timestamped](https://github.com/linto-ai/whisper-timestamped) has 2.8k stars, 210 forks, and 49 open issues, last pushed Sep 9, 2025. Figures are from public GitHub metadata via [ColossalAI's repository](https://github.com/hpcaitech/ColossalAI) and [whisper-timestamped's repository](https://github.com/linto-ai/whisper-timestamped). | | [ColossalAI](/tools/hpcaitech-colossalai.md) | [whisper-timestamped](/tools/linto-ai-whisper-timestamped.md) | | --- | --- | --- | | Tagline | Making large AI models cheaper, faster and more accessible | Multilingual Automatic Speech Recognition with word-level timestamps and confidence | | Stars | 41,408 | 2,823 | | Forks | 4,504 | 210 | | Open issues | 501 | 49 | | Language | Python | Python | | Adopt for | ColossalAI is a Python library that leverages advanced parallelism techniques for more efficient and cost-effective development of large-scale AI models. | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | AGPL-3.0 | | Categories | Inference & Serving, Model Training | Inference & Serving, Model Training, Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ColossalAI](/tools/hpcaitech-colossalai.md) | [whisper-timestamped](/tools/linto-ai-whisper-timestamped.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Slowing (36%) | | Days since push | 46d | 305d | | Open issues (now) | 501 | 49 | | Security scan | No lockfile | No criticals | | Full report | [trust report](/tools/hpcaitech-colossalai/trust.md) | [trust report](/tools/linto-ai-whisper-timestamped/trust.md) | ## Shared compatibility - **Python**: [ColossalAI](/tools/hpcaitech-colossalai.md) - Python runtime; [whisper-timestamped](/tools/linto-ai-whisper-timestamped.md) - Python runtime ## Decision facts: ColossalAI - **Adopt for:** ColossalAI is a Python library that leverages advanced parallelism techniques for more efficient and cost-effective development of large-scale AI models. ## Choose when ### Choose ColossalAI if… - License: ColossalAI is Apache-2.0, whisper-timestamped is AGPL-3.0. - 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. ### Choose whisper-timestamped if… - License: whisper-timestamped is AGPL-3.0, ColossalAI is Apache-2.0. - Tags unique to whisper-timestamped: asr, attention mechanism, attention-is-all-you-need, attention-model. - Also covers Speech & Audio. - whisper-timestamped ships Docker support for self-hosted deployment. ## 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. ## 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. - 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. ## 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, data-parallelism, distributed-computing; 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 mechanism, attention-is-all-you-need, attention-model; 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. 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 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](/tools/hpcaitech-colossalai/alternatives) and [whisper-timestamped alternatives](/tools/linto-ai-whisper-timestamped/alternatives) ([ColossalAI markdown twin](/tools/hpcaitech-colossalai/alternatives.md), [whisper-timestamped markdown twin](/tools/linto-ai-whisper-timestamped/alternatives.md)), 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](/compare/hpcaitech-colossalai-vs-linto-ai-whisper-timestamped.md) 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](/tools/hpcaitech-colossalai/trust); [whisper-timestamped trust report](/tools/linto-ai-whisper-timestamped/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=hpcaitech-colossalai`](/api/graphcanon/graph?tool=hpcaitech-colossalai) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_