Awesome GitHub RepositoriesMultilingual Code Models

Qwen3-Coder is a specialized large language model designed for software development, technical reasoning, and automated code synthesis. Built on transformer-based sequence modeling, it functions as a multilingual programming assistant capable of generating, completing, and debugging source code across more than one hundred programming languages. The model distinguishes itself through its capacity to process and maintain logical coherence across massive datasets, supporting context windows of up to one million tokens. This allows for repository-scale reasoning, enabling the model to analyze co

CodeGeeX is a multilingual large language model and AI code completion engine designed to generate, translate, and complete source code across numerous programming languages. It functions as an intelligence layer that synthesizes logic from natural language prompts and existing code snippets. The project provides a specialized source code translator that converts logic and functionality between different programming languages while preserving the original behavior. It also operates as an integrated AI assistant suite, offering extensions that embed generative AI directly into development envi

CodeGeeX is an open-source code model and multilingual large language model designed to generate, translate, and complete source code across multiple programming languages. It functions as an AI coding assistant and a cross-lingual code translator that produces executable code and technical documentation. The project enables natural language programming by turning plain English descriptions into functional programs. It also provides the ability to convert source code from one programming language to another while preserving the original logic and functionality. The system covers a range of c

CodeGeeX2 is a large language model and AI programming assistant designed to generate, translate, and document source code across multiple programming languages. It functions as a multilingual code model that converts natural language prompts into executable code and technical documentation. The project provides a self-hosted AI inference endpoint, allowing the model to be exposed as a web-accessible service. This enables external development tools to integrate automated programming tasks via network calls. Its core capabilities cover multilingual code generation, automated source code docum

SWE-bench is an automated evaluation framework that tests large language models on real-world software engineering tasks. It measures how effectively models can generate and apply code patches that resolve actual GitHub issues, using a standardized dataset and scoring system built around Docker-based patch verification against original project test suites. The framework provides curated benchmark datasets spanning comprehensive, fast, verified, multilingual, and multimodal evaluation splits, allowing targeted assessment of model capabilities across different programming languages and issue ty