--- title: "CodeGeeX vs GLM-130B" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/zai-org-codegeex-vs-zai-org-glm-130b" tools: ["zai-org-codegeex", "zai-org-glm-130b"] --- # CodeGeeX vs GLM-130B *GraphCanon updated Aug 2, 2026* ## Verdict Pick CodeGeeX if codeGeeX is an open-source multilingual code generation model, originally developed with MindSpore and compatible with PyTorch through DeepSpeed integration; pick GLM-130B if gLM-130B specializes in bilingual capabilities and is open source under the Apache-2.0 license. [CodeGeeX](https://codegeex.cn) reports 8.8k GitHub stars, 688 forks, and 188 open issues, last pushed Aug 13, 2024. [GLM-130B](https://github.com/zai-org/GLM-130B) has 7.7k stars, 600 forks, and 124 open issues, last pushed Jul 25, 2023. Figures are from public GitHub metadata via [CodeGeeX's repository](https://github.com/zai-org/CodeGeeX) and [GLM-130B's repository](https://github.com/zai-org/GLM-130B). | | [CodeGeeX](/tools/zai-org-codegeex.md) | [GLM-130B](/tools/zai-org-glm-130b.md) | | --- | --- | --- | | Tagline | CodeGeeX is an open multilingual code generation model implemented in Mindspore and available via PyTorch. | GLM-130B: An Open Bilingual Pre-Trained Model | | Stars | 8,809 | 7,656 | | Forks | 688 | 600 | | Open issues | 188 | 124 | | Language | Python | Python | | Adopt for | CodeGeeX is an open-source multilingual code generation model, originally developed with MindSpore and compatible with PyTorch through DeepSpeed integration. | GLM-130B specializes in bilingual capabilities and is open source under the Apache-2.0 license. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | The GLM-130B codebase and framework are available under the permissive Apache-2.0 license; however, usage of model weights is governed by its own Model License. | | Categories | LLM Frameworks, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [CodeGeeX](/tools/zai-org-codegeex.md) | [GLM-130B](/tools/zai-org-glm-130b.md) | | --- | --- | --- | | Days since push | 719d | 1103d | | Open issues (now) | 188 | 124 | | Full report | [trust report](/tools/zai-org-codegeex/trust.md) | [trust report](/tools/zai-org-glm-130b/trust.md) | ## Decision facts: CodeGeeX - **Adopt for:** CodeGeeX is an open-source multilingual code generation model, originally developed with MindSpore and compatible with PyTorch through DeepSpeed integration. ## Decision facts: GLM-130B - **Pricing:** freemium - Free to use with specific licensing requirements for model weights. - **Requirements:** Min 8 GB RAM - **Adopt for:** GLM-130B specializes in bilingual capabilities and is open source under the Apache-2.0 license. - **License detail:** The GLM-130B codebase and framework are available under the permissive Apache-2.0 license; however, usage of model weights is governed by its own Model License. ## Choose when ### Choose CodeGeeX if… - Tags unique to CodeGeeX: ai programming tools, code generation, pretrained-models. - When you require support for multilingual code generation and your project has a Python-based infrastructure with CUDA GPU availability. - More GitHub stars (8.8k vs 7.7k) - visibility, not fit. ### Choose GLM-130B if… - Pricing: Free to use with specific licensing requirements for model weights.. - Requirements: Min 8 GB RAM. - Tags unique to GLM-130B: bilingual, iclr 2023, language-model, pre-trained. - Use GLM-130B when you need strong support for two languages to facilitate multilingual content creation or processing, given its specialized training in bilingual contexts. ## When NOT to use CodeGeeX - If your development environment lacks the necessary dependencies like Python 3.7+, CUDA 11+, PyTorch 1.10+, and DeepSpeed 0.6+. - In scenarios where an open-source solution is not preferable or when support for exclusively one language's syntax is sufficient. ## When NOT to use GLM-130B - Avoid GLM-130B if your application demands single-language proficiency exclusively, as its strength lies specifically in bilingual support. - Do not use this model if you seek a resource with multilingual capabilities beyond two specific languages, since it focuses particularly on only a dual-language environment. ## Common questions ### What is the difference between CodeGeeX and GLM-130B? CodeGeeX: CodeGeeX is an open multilingual code generation model implemented in Mindspore and available via PyTorch.. GLM-130B: GLM-130B: An Open Bilingual Pre-Trained Model. See the comparison table for live GitHub stats and shared categories. ### When should I choose CodeGeeX over GLM-130B? Choose CodeGeeX over GLM-130B when Tags unique to CodeGeeX: ai programming tools, code generation, pretrained-models; When you require support for multilingual code generation and your project has a Python-based infrastructure with CUDA GPU availability; More GitHub stars (8.8k vs 7.7k) - visibility, not fit. ### When should I choose GLM-130B over CodeGeeX? Choose GLM-130B over CodeGeeX when Pricing: Free to use with specific licensing requirements for model weights.; Requirements: Min 8 GB RAM; Tags unique to GLM-130B: bilingual, iclr 2023, language-model, pre-trained; Use GLM-130B when you need strong support for two languages to facilitate multilingual content creation or processing, given its specialized training in bilingual contexts. ### When should I avoid CodeGeeX? If your development environment lacks the necessary dependencies like Python 3.7+, CUDA 11+, PyTorch 1.10+, and DeepSpeed 0.6+. In scenarios where an open-source solution is not preferable or when support for exclusively one language's syntax is sufficient. ### When should I avoid GLM-130B? Avoid GLM-130B if your application demands single-language proficiency exclusively, as its strength lies specifically in bilingual support. Do not use this model if you seek a resource with multilingual capabilities beyond two specific languages, since it focuses particularly on only a dual-language environment. ### Is CodeGeeX or GLM-130B more popular on GitHub? CodeGeeX has more GitHub stars (8,809 vs 7,656). Stars measure visibility, not whether either tool fits your constraints. ### Are CodeGeeX and GLM-130B open source? Yes - both are open-source projects on GitHub (CodeGeeX: Apache-2.0, GLM-130B: Apache-2.0). ### Where can I find alternatives to CodeGeeX or GLM-130B? GraphCanon lists graph-backed alternatives at [CodeGeeX alternatives](/tools/zai-org-codegeex/alternatives) and [GLM-130B alternatives](/tools/zai-org-glm-130b/alternatives) ([CodeGeeX markdown twin](/tools/zai-org-codegeex/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/zai-org-codegeex-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, CodeGeeX or GLM-130B? CodeGeeX: Dormant. 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 CodeGeeX and GLM-130B? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [CodeGeeX trust report](/tools/zai-org-codegeex/trust); [GLM-130B trust report](/tools/zai-org-glm-130b/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=zai-org-codegeex`](/api/graphcanon/graph?tool=zai-org-codegeex) - 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/_