--- title: "ColossalAI vs GLM-130B" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hpcaitech-colossalai-vs-zai-org-glm-130b" tools: ["hpcaitech-colossalai", "zai-org-glm-130b"] --- # ColossalAI vs GLM-130B *GraphCanon updated Jul 11, 2026* ## Verdict Pick ColossalAI when tags unique to ColossalAI: ai, big model, data-parallelism, deep-learning; pick GLM-130B when tags unique to GLM-130B: python. [ColossalAI](https://www.colossalai.org) reports 41k GitHub stars, 4.5k forks, and 501 open issues, last pushed May 25, 2026. [GLM-130B](https://github.com/zai-org/GLM-130B) has 7.7k stars, 601 forks, and 124 open issues, last pushed Jul 25, 2023. Figures are from public GitHub metadata via [ColossalAI's repository](https://github.com/hpcaitech/ColossalAI) and [GLM-130B's repository](https://github.com/zai-org/GLM-130B). | | [ColossalAI](/tools/hpcaitech-colossalai.md) | [GLM-130B](/tools/zai-org-glm-130b.md) | | --- | --- | --- | | Tagline | Making large AI models cheaper, faster and more accessible | GLM-130B: An Open Bilingual Pre-Trained Model (ICLR 2023) | | Stars | 41,408 | 7,656 | | Forks | 4,504 | 601 | | Open issues | 501 | 124 | | 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 | Apache-2.0 | | Categories | Inference & Serving, Model Training | Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ColossalAI](/tools/hpcaitech-colossalai.md) | [GLM-130B](/tools/zai-org-glm-130b.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Dormant (18%) | | Days since push | 46d | 1082d | | Open issues (now) | 501 | 124 | | Security scan | No lockfile | No criticals | | Full report | [trust report](/tools/hpcaitech-colossalai/trust.md) | [trust report](/tools/zai-org-glm-130b/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… - Tags unique to ColossalAI: ai, big model, data-parallelism, deep-learning. - Also covers Inference & Serving. - You require handling extremely large AI models with massive context windows, such as over 2M tokens. ### Choose GLM-130B if… - Tags unique to GLM-130B: python. - Leaner open-issue backlog (124). ## 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 GLM-130B - Last GitHub push was 1083 days ago (dormant maintenance, Jul 25, 2023). Validate activity before betting a new project on GLM-130B. - 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 GLM-130B? ColossalAI: Making large AI models cheaper, faster and more accessible. GLM-130B: GLM-130B: An Open Bilingual Pre-Trained Model (ICLR 2023). See the comparison table for live GitHub stats and shared categories. ### When should I choose ColossalAI over GLM-130B? Choose ColossalAI over GLM-130B when Tags unique to ColossalAI: ai, big model, data-parallelism, deep-learning; Also covers Inference & Serving; You require handling extremely large AI models with massive context windows, such as over 2M tokens. ### When should I choose GLM-130B over ColossalAI? Choose GLM-130B over ColossalAI when Tags unique to GLM-130B: python; Leaner open-issue backlog (124). ### 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 GLM-130B? Last GitHub push was 1083 days ago (dormant maintenance, Jul 25, 2023). Validate activity before betting a new project on GLM-130B. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ### Is ColossalAI or GLM-130B more popular on GitHub? ColossalAI has more GitHub stars (41,408 vs 7,656). Stars measure visibility, not whether either tool fits your constraints. ### Are ColossalAI and GLM-130B open source? Yes - both are open-source projects on GitHub (ColossalAI: Apache-2.0, GLM-130B: Apache-2.0). ### Where can I find alternatives to ColossalAI or GLM-130B? GraphCanon lists graph-backed alternatives at [ColossalAI alternatives](/tools/hpcaitech-colossalai/alternatives) and [GLM-130B alternatives](/tools/zai-org-glm-130b/alternatives) ([ColossalAI markdown twin](/tools/hpcaitech-colossalai/alternatives.md), [GLM-130B markdown twin](/tools/zai-org-glm-130b/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-zai-org-glm-130b.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ColossalAI or GLM-130B? ColossalAI: Steady. GLM-130B: 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 GLM-130B? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ColossalAI trust report](/tools/hpcaitech-colossalai/trust); [GLM-130B trust report](/tools/zai-org-glm-130b/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/_