--- title: "awesome-gpt3 vs CodeGeeX" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/elyase-awesome-gpt3-vs-zai-org-codegeex" tools: ["elyase-awesome-gpt3", "zai-org-codegeex"] --- # awesome-gpt3 vs CodeGeeX *GraphCanon updated Aug 6, 2026* ## Verdict Pick awesome-gpt3 if awesome-gpt3 is a curated collection of demonstrations and articles illustrating the capabilities of GPT-3 in various domains such as app design, data analysis, programming, and text generation; pick CodeGeeX if codeGeeX is an open-source multilingual code generation model, originally developed with MindSpore and compatible with PyTorch through DeepSpeed integration. [awesome-gpt3](https://github.com/elyase/awesome-gpt3) reports 4.5k GitHub stars, 345 forks, and 26 open issues, last pushed Aug 27, 2023. [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 [awesome-gpt3's repository](https://github.com/elyase/awesome-gpt3) and [CodeGeeX's repository](https://github.com/zai-org/CodeGeeX). | | [awesome-gpt3](/tools/elyase-awesome-gpt3.md) | [CodeGeeX](/tools/zai-org-codegeex.md) | | --- | --- | --- | | Tagline | A collection of demos and articles about the OpenAI GPT-3 API | CodeGeeX is an open multilingual code generation model implemented in Mindspore and available via PyTorch. | | Stars | 4,520 | 8,809 | | Forks | 345 | 688 | | Open issues | 26 | 188 | | Language | - | Python | | Adopt for | awesome-gpt3 is a curated collection of demonstrations and articles illustrating the capabilities of GPT-3 in various domains such as app design, data analysis, programming, and text generation. | CodeGeeX is an open-source multilingual code generation model, originally developed with MindSpore and compatible with PyTorch through DeepSpeed integration. | | Persona | - | - | | Runtime | - | - | | License | License information not specified, therefore usage rights are uncertain. | Apache-2.0 | | Categories | Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome-gpt3](/tools/elyase-awesome-gpt3.md) | [CodeGeeX](/tools/zai-org-codegeex.md) | | --- | --- | --- | | Maintenance | Archived (8%) | Dormant (18%) | | Days since push | 1075d | 719d | | Archived on GitHub | Yes | No | | Open issues (now) | 26 | 188 | | Owner type | User | Organization | | Full report | [trust report](/tools/elyase-awesome-gpt3/trust.md) | [trust report](/tools/zai-org-codegeex/trust.md) | ## Shared compatibility - **Python**: [awesome-gpt3](/tools/elyase-awesome-gpt3.md) - Python runtime; [CodeGeeX](/tools/zai-org-codegeex.md) - Python runtime ## Decision facts: awesome-gpt3 - **Requirements:** - No specific technical requirements stated except for engaging with GPT-3 through its API. - **Adopt for:** awesome-gpt3 is a curated collection of demonstrations and articles illustrating the capabilities of GPT-3 in various domains such as app design, data analysis, programming, and text generation. - **License detail:** License information not specified, therefore usage rights are uncertain. ## 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 awesome-gpt3 if… - Requirements: - No specific technical requirements stated except for engaging with GPT-3 through its API.. - Tags unique to awesome-gpt3: ai demos, gpt-3 applications. - - When you are looking for specific examples of how to leverage GPT-3's powerful API across different applications ranging from code generation to creative writing. ### Choose CodeGeeX if… - 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 awesome-gpt3 - - When seeking a direct development tool to integrate GPT-3 into your projects without further curation and customization. 'awesome-gpt3' is an example showcase rather than an SDK. - - If you require specific implementations for certain tasks like SEO optimization or language-specific translation beyond the provided samples, as it mainly contains links to tweets and external sites ## 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 awesome-gpt3 and CodeGeeX? awesome-gpt3: A collection of demos and articles about the OpenAI GPT-3 API. 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 awesome-gpt3 over CodeGeeX? Choose awesome-gpt3 over CodeGeeX when Requirements: - No specific technical requirements stated except for engaging with GPT-3 through its API.; Tags unique to awesome-gpt3: ai demos, gpt-3 applications; - When you are looking for specific examples of how to leverage GPT-3's powerful API across different applications ranging from code generation to creative writing. ### When should I choose CodeGeeX over awesome-gpt3? Choose CodeGeeX over awesome-gpt3 when 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 awesome-gpt3? - When seeking a direct development tool to integrate GPT-3 into your projects without further curation and customization. 'awesome-gpt3' is an example showcase rather than an SDK. - If you require specific implementations for certain tasks like SEO optimization or language-specific translation beyond the provided samples, as it mainly contains links to tweets and external sites ### 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 awesome-gpt3 or CodeGeeX more popular on GitHub? CodeGeeX has more GitHub stars (8,809 vs 4,520). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome-gpt3 and CodeGeeX open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to awesome-gpt3 or CodeGeeX? GraphCanon lists graph-backed alternatives at [awesome-gpt3 alternatives](/tools/elyase-awesome-gpt3/alternatives) and [CodeGeeX alternatives](/tools/zai-org-codegeex/alternatives) ([awesome-gpt3 markdown twin](/tools/elyase-awesome-gpt3/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/elyase-awesome-gpt3-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, awesome-gpt3 or CodeGeeX? awesome-gpt3: Archived. 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 awesome-gpt3 and CodeGeeX? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-gpt3 trust report](/tools/elyase-awesome-gpt3/trust); [CodeGeeX trust report](/tools/zai-org-codegeex/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=elyase-awesome-gpt3`](/api/graphcanon/graph?tool=elyase-awesome-gpt3) - 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/_