--- title: "Hands-On-Large-Language-Models vs CodeGeeX" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/handsonllm-hands-on-large-language-models-vs-zai-org-codegeex" tools: ["handsonllm-hands-on-large-language-models", "zai-org-codegeex"] --- # Hands-On-Large-Language-Models vs CodeGeeX *GraphCanon updated Aug 16, 2026* ## Verdict Pick Hands-On-Large-Language-Models if consider using the 'Hands-On-Large-Language-Models' repository if your interest aligns with hands-on learning and practice of large language models through coding examples; pick CodeGeeX if codeGeeX is an open-source multilingual code generation model, originally developed with MindSpore and compatible with PyTorch through DeepSpeed integration. [Hands-On-Large-Language-Models](https://www.llm-book.com/) reports 28k GitHub stars, 6.5k forks, and 38 open issues, last pushed Apr 24, 2026. [CodeGeeX](https://codegeex.cn) has 8.8k stars, 688 forks, and 188 open issues, last pushed Aug 13, 2024. Figures are from public GitHub metadata via [Hands-On-Large-Language-Models's repository](https://github.com/HandsOnLLM/Hands-On-Large-Language-Models) and [CodeGeeX's repository](https://github.com/zai-org/CodeGeeX). | | [Hands-On-Large-Language-Models](/tools/handsonllm-hands-on-large-language-models.md) | [CodeGeeX](/tools/zai-org-codegeex.md) | | --- | --- | --- | | Tagline | Official code repo for the O'Reilly Book - 'Hands-On Large Language Models' | CodeGeeX is an open multilingual code generation model implemented in Mindspore and available via PyTorch. | | Stars | 28,252 | 8,809 | | Forks | 6,531 | 688 | | Open issues | 38 | 188 | | Language | Jupyter Notebook | Python | | Adopt for | Consider using the 'Hands-On-Large-Language-Models' repository if your interest aligns with hands-on learning and practice of large language models through coding examples. | CodeGeeX is an open-source multilingual code generation model, originally developed with MindSpore and compatible with PyTorch through DeepSpeed integration. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 License | Apache-2.0 | | Categories | LLM Frameworks, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Hands-On-Large-Language-Models](/tools/handsonllm-hands-on-large-language-models.md) | [CodeGeeX](/tools/zai-org-codegeex.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Dormant (18%) | | Days since push | 114d | 719d | | Open issues (now) | 38 | 188 | | Stars delta | +642 (30d) | Unknown | | Open issues delta | 0 (30d) | Unknown | | Full report | [trust report](/tools/handsonllm-hands-on-large-language-models/trust.md) | [trust report](/tools/zai-org-codegeex/trust.md) | ## Decision facts: Hands-On-Large-Language-Models - **Pricing:** freemium - The repository is free and open under the Apache-2.0 license. - **Requirements:** - Access to Jupyter Notebook is required for running code examples provided in this repository.; - Fundamental understanding of large language models and familiarity with AI concepts would be beneficial. - **Adopt for:** Consider using the 'Hands-On-Large-Language-Models' repository if your interest aligns with hands-on learning and practice of large language models through coding examples. - **License detail:** Apache-2.0 License ## 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. ## Choose when ### Choose Hands-On-Large-Language-Models if… - Hands-On-Large-Language-Models is primarily Jupyter Notebook; CodeGeeX is Python. - Pricing: The repository is free and open under the Apache-2.0 license.. - Requirements: - Access to Jupyter Notebook is required for running code examples provided in this repository.; - Fundamental understanding of large language models and familiarity with AI concepts would be beneficial.. - Tags unique to Hands-On-Large-Language-Models: artificial-intelligence, book, large language models, llm. - - You are focusing on practical implementation aspects detailed in a structured format as outlined by O'Reilly's authoritative book. ### Choose CodeGeeX if… - CodeGeeX is primarily Python; Hands-On-Large-Language-Models is Jupyter Notebook. - 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. ## When NOT to use Hands-On-Large-Language-Models - - If you need real-time model evaluation tools rather than educational materials, as this repository primarily provides code for understanding and implementing concepts covered in a book. - - You are seeking proprietary or more specialized frameworks that go beyond the examples provided in an educational context to meet specific, advanced use-case needs. ## 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. ## Common questions ### What is the difference between Hands-On-Large-Language-Models and CodeGeeX? Hands-On-Large-Language-Models: Official code repo for the O'Reilly Book - 'Hands-On Large Language Models'. CodeGeeX: CodeGeeX is an open multilingual code generation model implemented in Mindspore and available via PyTorch.. See the comparison table for live GitHub stats and shared categories. ### When should I choose Hands-On-Large-Language-Models over CodeGeeX? Choose Hands-On-Large-Language-Models over CodeGeeX when Hands-On-Large-Language-Models is primarily Jupyter Notebook; CodeGeeX is Python; Pricing: The repository is free and open under the Apache-2.0 license.; Requirements: - Access to Jupyter Notebook is required for running code examples provided in this repository.; - Fundamental understanding of large language models and familiarity with AI concepts would be beneficial.; Tags unique to Hands-On-Large-Language-Models: artificial-intelligence, book, large language models, llm; - You are focusing on practical implementation aspects detailed in a structured format as outlined by O'Reilly's authoritative book. ### When should I choose CodeGeeX over Hands-On-Large-Language-Models? Choose CodeGeeX over Hands-On-Large-Language-Models when CodeGeeX is primarily Python; Hands-On-Large-Language-Models is Jupyter Notebook; 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. ### When should I avoid Hands-On-Large-Language-Models? - If you need real-time model evaluation tools rather than educational materials, as this repository primarily provides code for understanding and implementing concepts covered in a book. - You are seeking proprietary or more specialized frameworks that go beyond the examples provided in an educational context to meet specific, advanced use-case needs. ### 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. ### Is Hands-On-Large-Language-Models or CodeGeeX more popular on GitHub? Hands-On-Large-Language-Models has more GitHub stars (28,252 vs 8,809). Stars measure visibility, not whether either tool fits your constraints. ### Are Hands-On-Large-Language-Models and CodeGeeX open source? Yes - both are open-source projects on GitHub (Hands-On-Large-Language-Models: Apache-2.0, CodeGeeX: Apache-2.0). ### Where can I find alternatives to Hands-On-Large-Language-Models or CodeGeeX? GraphCanon lists graph-backed alternatives at [Hands-On-Large-Language-Models alternatives](/tools/handsonllm-hands-on-large-language-models/alternatives) and [CodeGeeX alternatives](/tools/zai-org-codegeex/alternatives) ([Hands-On-Large-Language-Models markdown twin](/tools/handsonllm-hands-on-large-language-models/alternatives.md), [CodeGeeX markdown twin](/tools/zai-org-codegeex/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/handsonllm-hands-on-large-language-models-vs-zai-org-codegeex.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Hands-On-Large-Language-Models or CodeGeeX? Hands-On-Large-Language-Models: Slowing. CodeGeeX: 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 Hands-On-Large-Language-Models and CodeGeeX? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Hands-On-Large-Language-Models trust report](/tools/handsonllm-hands-on-large-language-models/trust); [CodeGeeX trust report](/tools/zai-org-codegeex/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=handsonllm-hands-on-large-language-models`](/api/graphcanon/graph?tool=handsonllm-hands-on-large-language-models) - 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/_