--- title: "octopack vs CodeGeeX" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/bigcode-project-octopack-vs-zai-org-codegeex" tools: ["bigcode-project-octopack", "zai-org-codegeex"] --- # octopack vs CodeGeeX *GraphCanon updated Aug 5, 2026* ## Verdict Pick octopack if octoPack is an instruction tuning code large language models repository providing detailed components for model training with data retrieval; pick CodeGeeX if codeGeeX is an open-source multilingual code generation model, originally developed with MindSpore and compatible with PyTorch through DeepSpeed integration. [octopack](https://arxiv.org/abs/2308.07124) reports 479 GitHub stars, 29 forks, and 14 open issues, last pushed Feb 5, 2025. [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 [octopack's repository](https://github.com/bigcode-project/octopack) and [CodeGeeX's repository](https://github.com/zai-org/CodeGeeX). | | [octopack](/tools/bigcode-project-octopack.md) | [CodeGeeX](/tools/zai-org-codegeex.md) | | --- | --- | --- | | Tagline | OctoPack: Instruction Tuning Code Large Language Models | CodeGeeX is an open multilingual code generation model implemented in Mindspore and available via PyTorch. | | Stars | 479 | 8,809 | | Forks | 29 | 688 | | Open issues | 14 | 188 | | Language | Jupyter Notebook | Python | | Adopt for | OctoPack is an instruction tuning code large language models repository providing detailed components for model training with data retrieval. | CodeGeeX is an open-source multilingual code generation model, originally developed with MindSpore and compatible with PyTorch through DeepSpeed integration. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Data & Retrieval, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [octopack](/tools/bigcode-project-octopack.md) | [CodeGeeX](/tools/zai-org-codegeex.md) | | --- | --- | --- | | Days since push | 545d | 719d | | Open issues (now) | 14 | 188 | | Full report | [trust report](/tools/bigcode-project-octopack/trust.md) | [trust report](/tools/zai-org-codegeex/trust.md) | ## Decision facts: octopack - **Adopt for:** OctoPack is an instruction tuning code large language models repository providing detailed components for model training with data retrieval. ## 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 octopack if… - octopack is primarily Jupyter Notebook; CodeGeeX is Python. - License: octopack is MIT, CodeGeeX is Apache-2.0. - Tags unique to octopack: code-llm, dataset, evaluation, instruction-tuning. - Also covers Data & Retrieval. - When you need to fine-tune StarCoder or CodeGeeX2 on commit message datasets formatted as instructions ### Choose CodeGeeX if… - CodeGeeX is primarily Python; octopack is Jupyter Notebook. - License: CodeGeeX is Apache-2.0, octopack is MIT. - Tags unique to CodeGeeX: ai programming tools, code generation, pretrained-models. - Also covers LLM Frameworks. - When you require support for multilingual code generation and your project has a Python-based infrastructure with CUDA GPU availability. ## When NOT to use octopack - If your project does not require instruction tuning and focuses solely on general model improvements - When your data source is limited to English or a few languages, excluding the need for broad linguistic coverage as provided by CommitPack ## 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 octopack and CodeGeeX? octopack: OctoPack: Instruction Tuning Code 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 octopack over CodeGeeX? Choose octopack over CodeGeeX when octopack is primarily Jupyter Notebook; CodeGeeX is Python; License: octopack is MIT, CodeGeeX is Apache-2.0; Tags unique to octopack: code-llm, dataset, evaluation, instruction-tuning; Also covers Data & Retrieval; When you need to fine-tune StarCoder or CodeGeeX2 on commit message datasets formatted as instructions. ### When should I choose CodeGeeX over octopack? Choose CodeGeeX over octopack when CodeGeeX is primarily Python; octopack is Jupyter Notebook; License: CodeGeeX is Apache-2.0, octopack is MIT; Tags unique to CodeGeeX: ai programming tools, code generation, pretrained-models; Also covers LLM Frameworks; When you require support for multilingual code generation and your project has a Python-based infrastructure with CUDA GPU availability. ### When should I avoid octopack? If your project does not require instruction tuning and focuses solely on general model improvements When your data source is limited to English or a few languages, excluding the need for broad linguistic coverage as provided by CommitPack ### 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 octopack or CodeGeeX more popular on GitHub? CodeGeeX has more GitHub stars (8,809 vs 479). Stars measure visibility, not whether either tool fits your constraints. ### Are octopack and CodeGeeX open source? Yes - both are open-source projects on GitHub (octopack: MIT, CodeGeeX: Apache-2.0). ### Where can I find alternatives to octopack or CodeGeeX? GraphCanon lists graph-backed alternatives at [octopack alternatives](/tools/bigcode-project-octopack/alternatives) and [CodeGeeX alternatives](/tools/zai-org-codegeex/alternatives) ([octopack markdown twin](/tools/bigcode-project-octopack/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/bigcode-project-octopack-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, octopack or CodeGeeX? octopack: Dormant. 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 octopack and CodeGeeX? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [octopack trust report](/tools/bigcode-project-octopack/trust); [CodeGeeX trust report](/tools/zai-org-codegeex/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=bigcode-project-octopack`](/api/graphcanon/graph?tool=bigcode-project-octopack) - 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/_