Open-source alternatives to DeepSeek Coder

Sglang is a high-performance inference engine and serving system designed for large language and multimodal models. It provides a programmable interface for orchestrating complex generation workflows, enabling developers to coordinate multi-turn dialogues, tool invocations, and reasoning chains through a domain-specific language. The platform is built to support production-scale deployments, offering an OpenAI-compatible API that allows for integration with existing application ecosystems. The system distinguishes itself through a disaggregated architecture that separates compute-intensive pr

GLM-4.5 is a multimodal large language model and advanced reasoning system. It functions as an AI coding assistant, an autonomous AI agent, and a multimodal content generator capable of processing and generating text, images, audio, and video within a single unified system. The project is distinguished by its deep reasoning capabilities, utilizing chain-of-thought processing to solve complex mathematical, logical, and technical problems. It features an agentic architecture that allows for autonomous task execution, long-horizon goal planning, and the ability to interact with external tools an

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

This project is an educational platform and research toolkit designed to teach deep learning through a combination of mathematical theory, visual diagrams, and executable code. It provides a comprehensive environment for building, training, and evaluating neural networks, grounding complex concepts in interactive computational notebooks that allow for hands-on experimentation. The framework distinguishes itself by interleaving theoretical foundations—including linear algebra, calculus, and probability—with practical implementations across multiple industry-standard libraries. It supports flex

This project is a Vim plugin that functions as an AI-powered coding assistant. It integrates large language models directly into the text editor to provide real-time code suggestions and function completions based on the current file context and cursor position. The plugin distinguishes itself by utilizing an asynchronous event loop to maintain editor responsiveness while communicating with remote models. It employs a virtual buffer overlay to display generated code suggestions, allowing users to preview and accept proposed changes without modifying the underlying file until explicitly confir

CopilotForXcode is an AI source editor extension for the Xcode development environment. It provides a suite of tools including a conversational chat interface, a code completion tool, and a natural language refactorer to assist with Apple platform development. The project differentiates itself by integrating project context and compiler errors directly into its AI interactions. It supports custom prompt execution using template variables and enables the triggering of shell scripts and system shortcuts directly from the chat interface to automate development tasks. The system manages AI integ

Positron is a data science integrated development environment and AI-powered code editor designed for polyglot development, specifically supporting Python and R. It functions as a remote compute workspace that separates the user interface from the execution kernel via SSH or container integration. The environment features a deep integration of large language models that provide context-aware suggestions and automated data analysis by accessing real-time interpreter state, in-memory objects, and plot outputs. It distinguishes itself through a polyglot runtime bridge that enables cross-language

GitHub Copilot is an AI-powered development platform designed to integrate large language models directly into coding environments. It functions as an interactive assistant and an agentic workflow orchestrator, enabling developers to automate code generation, perform automated code reviews, and execute complex, multi-step development tasks through natural language prompts. The platform distinguishes itself through its autonomous agent capabilities, which allow for repository-level research, implementation planning, and code modifications across multiple files. It supports a modular architectu

Refact is an autonomous AI software engineering system and code assistant. It functions as an agent orchestrator capable of planning, executing, and managing multi-step development workflows to complete complex software tasks independently. The system distinguishes itself through agentic state management, using isolated worktrees and versioned checkpoints to allow autonomous agents to experiment with code changes and roll back to stable states if tasks fail. It further extends its capabilities via the Model Context Protocol, connecting the AI engine to external databases, version control syst

Qwen2.5 is a suite of large language model foundation models designed for natural language generation, code production, and complex mathematical reasoning. The project encompasses a multilingual language model capable of processing dozens of languages and a specialized code generation model for technical problem solving and debugging. The framework is distinguished by its long context capabilities, enabling the analysis of massive inputs ranging from 256K up to 1 million tokens. It further functions as an agentic framework, utilizing standardized templates and parsers to execute autonomous wo

Cursor is an artificial intelligence-powered code editor built as a fork of the Visual Studio Code environment. It integrates machine learning models directly into the development workflow, allowing users to generate, refactor, and debug code through natural language prompts while maintaining full compatibility with existing editor extensions and themes. The editor distinguishes itself through a specialized codebase context engine that indexes local project structures and file relationships using vector-based embeddings. This system enables the editor to inject relevant file snippets and proj

Cursor is an AI-powered code editor and integrated development environment built as a fork of Visual Studio Code. It functions as an AI programming assistant that integrates large language models directly into the editing experience to write, refactor, and maintain source code. The editor utilizes a customized version of the VS Code interface to provide native artificial intelligence capabilities, including an environment for natural language code generation and codebase indexing. The platform covers a range of AI-assisted coding capabilities, such as intelligent code completion, automated c

Qwen2.5-Coder is a code-centric large language model designed to generate, complete, and analyze source code. It serves as a polyglot programming model capable of producing functional code across hundreds of different programming languages. The model is optimized for reasoning over extensive software repositories, utilizing a context window that supports up to one million tokens. It also functions as an agentic coding framework, executing multi-step workflows and browser tasks through specialized function call formats. Its capabilities include large-scale codebase analysis, intelligent parti

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

CodeQwen1.5 is a large language model designed for generating, completing, and analyzing code. It functions as an AI code generator capable of writing programming logic across hundreds of different languages. The model is distinguished by its long-context capabilities, allowing it to process up to one million tokens to reason across entire software repositories. It also operates as a function calling model, utilizing specialized formats to execute complex coding tasks and browser-based automation. The system supports intelligent code completion through fill-in-the-middle capabilities, which

Roo-Code is an integrated development environment extension that functions as an autonomous software engineering agent. It connects large language models directly to your local file system and terminal, enabling the agent to interpret natural language requirements and execute complex development workflows. The project distinguishes itself through a model-agnostic orchestration layer that allows developers to connect various large language model backends to their local workspace. By utilizing an iterative tool-use loop, the agent decomposes high-level tasks into sequential steps, interacting w

Qwen-code is an AI-powered development framework designed for orchestrating intelligent coding agents within terminal and IDE environments. It provides a comprehensive infrastructure for automating software maintenance, code generation, and complex refactoring tasks by managing multi-agent workflows and persistent session states. The system is built to handle both interactive development and automated background processes, ensuring that agents can execute shell commands and file operations safely within isolated, sandboxed environments. What distinguishes this project is its focus on granular

CodeGen is a trained large language model and program synthesis model designed to generate functional source code. It utilizes a neural network architecture to synthesize executable code from natural language descriptions or partial code snippets. The model enables automated program synthesis and AI-assisted coding by predicting and filling in missing sections of code within a program. It transforms natural language descriptions into functional programming logic to automate the creation of boilerplate and logic.

This project is a high-performance library for converting raw text into tokens and IDs for machine learning models. It functions as a fast text encoder and a text preprocessing pipeline designed to transform strings into numerical representations with high throughput for research and production. The library includes a subword tokenizer trainer used to analyze text datasets and create custom vocabularies using algorithms such as byte-pair encoding and wordpiece. It provides capabilities for subword vocabulary training and text alignment, allowing character offsets to be tracked during normaliz

Plandex is an AI-powered software development platform that operates as a command-line interface to manage complex, long-running coding tasks. It functions as an automated agent that decomposes high-level programming objectives into granular, actionable steps, executing multi-file code changes directly within a local project environment. The system distinguishes itself through a state-machine-based execution model that tracks progress across iterative development cycles. By utilizing context-aware code indexing and an iterative feedback loop, the tool refines generated code through successive

Fairseq is a PyTorch toolkit for sequence-to-sequence modeling, specializing in neural machine translation, automatic speech recognition, and large-scale language model training. It provides a framework for processing and aligning diverse data sources, including text, audio, and video, to support tasks such as speech-to-text conversion and multimodal sequence learning. The project is distinguished by its distributed training capabilities, which utilize parameter sharding, mixed-precision training, and CPU offloading to handle models that exceed single-device memory. It also includes specializ

SentencePiece is a text segmentation engine and tokenization library designed for machine learning workflows. It provides a comprehensive toolkit for transforming raw text into subword units or numerical identifiers, enabling consistent data representation for neural network training and inference. The library supports the training of segmentation models from raw text, allowing for the creation of custom vocabularies tailored to specific domain requirements. The project distinguishes itself through its byte-level encoding and fallback mechanisms, which ensure that every input can be represent

Qwen is a comprehensive framework for large language model development, serving, and deployment. It provides a complete ecosystem for transformer-based sequence modeling, offering base models alongside specialized tools for instruction-tuned alignment, fine-tuning, and long-context inference. The project is designed to support both research and production environments, enabling users to train, optimize, and host generative models locally or across distributed hardware. The framework distinguishes itself through its focus on high-performance serving and extensibility. It features a high-perfor

Llama 3 is a collection of pretrained, autoregressive transformer-based models designed for natural language generation, reasoning, and complex instruction following. It functions as a generative AI framework that provides the infrastructure for managing model weights, executing neural network inference, and handling computational workloads across diverse knowledge domains. The project distinguishes itself through an integrated AI safety toolkit that employs secondary classification filtering to inspect inputs and outputs, ensuring adherence to usage compliance and safety standards. It suppor

This repository serves as a comprehensive collection of reference implementations for the PyTorch machine learning library. It provides practical examples for building, training, and deploying deep learning models, functioning as a toolkit for developers to explore neural network architectures and training workflows. The project distinguishes itself by offering concrete demonstrations of complex machine learning operations, ranging from computer vision tasks like object detection and depth estimation to the training of large-scale transformer models. These examples illustrate how to implement

This project serves as a curated directory and resource hub for developers working with generative artificial intelligence. It provides a comprehensive index of open-source software solutions, frameworks, and project examples designed to help users discover and implement advanced AI systems. The repository focuses on practical implementations of agentic, multimodal, and retrieval-augmented generation architectures. It highlights tools for building conversational assistants, voice-enabled agents, and automated workflows that leverage large language models. By showcasing diverse technical domai

jetson-inference is a set of libraries and tools for executing optimized deep learning models on embedded GPU hardware. Its primary purpose is to enable real-time computer vision and AI inference at the edge with low latency and high throughput. The project distinguishes itself through high-performance streaming analytics and the ability to execute concurrent AI pipelines on auto-grade silicon. It provides specialized support for multi-sensor stream processing, utilizing zero-copy data transport to load camera frames directly into GPU memory. The codebase covers a broad surface of capabiliti