--- title: "ColossalAI vs pai" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hpcaitech-colossalai-vs-microsoft-pai" tools: ["hpcaitech-colossalai", "microsoft-pai"] --- # ColossalAI vs pai *GraphCanon updated Jul 11, 2026* ## Verdict Pick ColossalAI when colossalAI is primarily Python; pai is JavaScript; pick pai when pai is primarily JavaScript; ColossalAI is Python. [ColossalAI](https://www.colossalai.org) reports 41k GitHub stars, 4.5k forks, and 501 open issues, last pushed May 25, 2026. [pai](https://openpai.readthedocs.io) has 2.7k stars, 549 forks, and 282 open issues, last pushed Jun 6, 2024. Figures are from public GitHub metadata via [ColossalAI's repository](https://github.com/hpcaitech/ColossalAI) and [pai's repository](https://github.com/microsoft/pai). | | [ColossalAI](/tools/hpcaitech-colossalai.md) | [pai](/tools/microsoft-pai.md) | | --- | --- | --- | | Tagline | Making large AI models cheaper, faster and more accessible | Resource scheduling and cluster management for AI | | Stars | 41,408 | 2,683 | | Forks | 4,504 | 549 | | Open issues | 501 | 282 | | Language | Python | JavaScript | | 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 | MIT | | Categories | Inference & Serving, Model Training | Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ColossalAI](/tools/hpcaitech-colossalai.md) | [pai](/tools/microsoft-pai.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Archived (8%) | | Days since push | 46d | 765d | | Archived on GitHub | No | Yes | | Open issues (now) | 501 | 282 | | Full report | [trust report](/tools/hpcaitech-colossalai/trust.md) | [trust report](/tools/microsoft-pai/trust.md) | ## 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; pai is JavaScript. - License: ColossalAI is Apache-2.0, pai is MIT. - Tags unique to ColossalAI: big-model, data-parallelism, deep-learning, distributed-computing. - Also covers Inference & Serving. - You require handling extremely large AI models with massive context windows, such as over 2M tokens. ### Choose pai if… - pai is primarily JavaScript; ColossalAI is Python. - License: pai is MIT, ColossalAI is Apache-2.0. - Tags unique to pai: artificial-intelligence, chainer, cloud, cluster-management. ## 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 pai - pai is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency. - 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 pai? ColossalAI: Making large AI models cheaper, faster and more accessible. pai: Resource scheduling and cluster management for AI. See the comparison table for live GitHub stats and shared categories. ### When should I choose ColossalAI over pai? Choose ColossalAI over pai when ColossalAI is primarily Python; pai is JavaScript; License: ColossalAI is Apache-2.0, pai is MIT; Tags unique to ColossalAI: big-model, data-parallelism, deep-learning, distributed-computing; Also covers Inference & Serving; You require handling extremely large AI models with massive context windows, such as over 2M tokens. ### When should I choose pai over ColossalAI? Choose pai over ColossalAI when pai is primarily JavaScript; ColossalAI is Python; License: pai is MIT, ColossalAI is Apache-2.0; Tags unique to pai: artificial-intelligence, chainer, cloud, cluster-management. ### 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 pai? pai is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ### Is ColossalAI or pai more popular on GitHub? ColossalAI has more GitHub stars (41,408 vs 2,683). Stars measure visibility, not whether either tool fits your constraints. ### Are ColossalAI and pai open source? Yes - both are open-source projects on GitHub (ColossalAI: Apache-2.0, pai: MIT). ### Where can I find alternatives to ColossalAI or pai? GraphCanon lists graph-backed alternatives at [ColossalAI alternatives](/tools/hpcaitech-colossalai/alternatives) and [pai alternatives](/tools/microsoft-pai/alternatives) ([ColossalAI markdown twin](/tools/hpcaitech-colossalai/alternatives.md), [pai markdown twin](/tools/microsoft-pai/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-microsoft-pai.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ColossalAI or pai? ColossalAI: Steady. pai: Archived. 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 pai? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ColossalAI trust report](/tools/hpcaitech-colossalai/trust); [pai trust report](/tools/microsoft-pai/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/_