--- title: "ColossalAI vs whylogs" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hpcaitech-colossalai-vs-whylabs-whylogs" tools: ["hpcaitech-colossalai", "whylabs-whylogs"] --- # ColossalAI vs whylogs *GraphCanon updated Jul 11, 2026* ## Verdict Pick ColossalAI when colossalAI is primarily Python; whylogs is Jupyter Notebook; pick whylogs when whylogs is primarily Jupyter Notebook; ColossalAI is Python. [ColossalAI](https://www.colossalai.org) reports 41k GitHub stars, 4.5k forks, and 501 open issues, last pushed May 25, 2026. [whylogs](https://whylogs.readthedocs.io/) has 2.8k stars, 143 forks, and 4 open issues, last pushed Jan 10, 2025. Figures are from public GitHub metadata via [ColossalAI's repository](https://github.com/hpcaitech/ColossalAI) and [whylogs's repository](https://github.com/whylabs/whylogs). | | [ColossalAI](/tools/hpcaitech-colossalai.md) | [whylogs](/tools/whylabs-whylogs.md) | | --- | --- | --- | | Tagline | Making large AI models cheaper, faster and more accessible | An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collect | | Stars | 41,408 | 2,826 | | Forks | 4,504 | 143 | | Open issues | 501 | 4 | | Language | Python | Jupyter Notebook | | 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 | Apache-2.0 | | Categories | Inference & Serving, Model Training | Computer Vision, Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ColossalAI](/tools/hpcaitech-colossalai.md) | [whylogs](/tools/whylabs-whylogs.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Dormant (18%) | | Days since push | 46d | 547d | | Open issues (now) | 501 | 4 | | Full report | [trust report](/tools/hpcaitech-colossalai/trust.md) | [trust report](/tools/whylabs-whylogs/trust.md) | ## Shared compatibility - **Python**: [ColossalAI](/tools/hpcaitech-colossalai.md) - Python runtime; [whylogs](/tools/whylabs-whylogs.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… - ColossalAI is primarily Python; whylogs is Jupyter Notebook. - Tags unique to ColossalAI: ai, big-model, data-parallelism, deep-learning. - You require handling extremely large AI models with massive context windows, such as over 2M tokens. ### Choose whylogs if… - whylogs is primarily Jupyter Notebook; ColossalAI is Python. - Tags unique to whylogs: ai-pipelines, analytics, approximate-statistics, calculate-statistics. - Also covers Computer Vision. - whylogs 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 whylogs - Last GitHub push was 547 days ago (dormant maintenance, Jan 10, 2025). Validate activity before betting a new project on whylogs. - 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 whylogs? ColossalAI: Making large AI models cheaper, faster and more accessible. whylogs: An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collect. See the comparison table for live GitHub stats and shared categories. ### When should I choose ColossalAI over whylogs? Choose ColossalAI over whylogs when ColossalAI is primarily Python; whylogs is Jupyter Notebook; Tags unique to ColossalAI: ai, big-model, data-parallelism, deep-learning; You require handling extremely large AI models with massive context windows, such as over 2M tokens. ### When should I choose whylogs over ColossalAI? Choose whylogs over ColossalAI when whylogs is primarily Jupyter Notebook; ColossalAI is Python; Tags unique to whylogs: ai-pipelines, analytics, approximate-statistics, calculate-statistics; Also covers Computer Vision; whylogs 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 whylogs? Last GitHub push was 547 days ago (dormant maintenance, Jan 10, 2025). Validate activity before betting a new project on whylogs. 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 whylogs more popular on GitHub? ColossalAI has more GitHub stars (41,408 vs 2,826). Stars measure visibility, not whether either tool fits your constraints. ### Are ColossalAI and whylogs open source? Yes - both are open-source projects on GitHub (ColossalAI: Apache-2.0, whylogs: Apache-2.0). ### Where can I find alternatives to ColossalAI or whylogs? GraphCanon lists graph-backed alternatives at [ColossalAI alternatives](/tools/hpcaitech-colossalai/alternatives) and [whylogs alternatives](/tools/whylabs-whylogs/alternatives) ([ColossalAI markdown twin](/tools/hpcaitech-colossalai/alternatives.md), [whylogs markdown twin](/tools/whylabs-whylogs/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-whylabs-whylogs.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ColossalAI or whylogs? ColossalAI: Steady. whylogs: 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 whylogs? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ColossalAI trust report](/tools/hpcaitech-colossalai/trust); [whylogs trust report](/tools/whylabs-whylogs/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/_