CodeGeeX

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About CodeGeeX

Open‑source 13B parameter multilingual code generation model – strong in generation, translation & explanation.

CodeGeeX is a large‑scale multilingual code generation model with around 13 billion parameters developed for researchers and developers who need powerful tools for writing, translating, completing, and explaining code across many programming languages. Trained on over 850 billion tokens spanning 23 programming languages, CodeGeeX demonstrates strong performance on multilingual tasks including code generation and cross‑language translation. Its architecture features 40 transformer layers, a hidden size of ~5,120 for self‑attention blocks and ~20,480 for feed‑forward networks, allowing it to process long contexts and maintain semantic consistency across files. The model supports a maximum sequence length of approximately 2,048 tokens. To help evaluate and benchmark its multilingual capabilities, the creators introduced the HumanEval‑X benchmark: 820 problems written in 5 languages (Python, C++, Java, JavaScript, Go), each with corresponding test suites. In benchmark testing, CodeGeeX outperforms many open‑source models of similar scale in both functional correctness and translation accuracy. In addition to being available as model weights, CodeGeeX is offered as extensions/plugins for popular IDEs like VS Code, JetBrains IDEs; users can get features such as code completion, summarization, explanation of code snippets, translation between languages, and natural‑language to code generation. The tool is open source with public model weights, supporting both Ascend 910 and NVIDIA hardware platforms, as well as local inference. The community around CodeGeeX reports high usefulness: many users say it improves productivity, helps reduce boilerplate, and assists in learning by helping explain code. Drawbacks include resource demands (running the 13B model requires significant memory / GPU resources), latency when using large contexts, less polished tooling compared to commercial platforms for things like interactive help or dashboards, and occasional quality dips in less common languages or edge cases. For teams and enterprise users, private deployment or special infrastructure may be needed. Overall, CodeGeeX is a strong option for those valuing openness, multilingual capacity, and research / experimentation, or needing cross‑language support, though it may require more engineering effort to deploy at large scale.

Key Features

Example Prompts