CodeGPT vs. Gemini Code Assist vs. JavaScript vs. StarCoder Comparison Chart

Increase software development and delivery velocity using generative AI assistance, with enterprise security and privacy protection. Gemini Code Assist completes your code as you write, and generates whole code blocks or functions on demand. Code assistance is available in many popular IDEs, such as Visual Studio Code, JetBrains IDEs (IntelliJ, PyCharm, GoLand, WebStorm, and more), Cloud Workstations, Cloud Shell Editor, and supports 20+ programming languages, including Java, JavaScript, Python, C, C++, Go, PHP, and SQL. Through a natural language chat interface, you can quickly chat with Gemini Code Assist to get answers to your coding questions, or receive guidance on coding best practices. Chat is available in all supported IDEs. Enterprises can customize Gemini Code Assist using their organization’s private codebases and knowledge sources so that Gemini Code Assist can offer more tailored assistance. Gemini Code Assist enables large-scale changes to entire codebases.

StarCoder and StarCoderBase are Large Language Models for Code (Code LLMs) trained on permissively licensed data from GitHub, including from 80+ programming languages, Git commits, GitHub issues, and Jupyter notebooks. Similar to LLaMA, we trained a ~15B parameter model for 1 trillion tokens. We fine-tuned StarCoderBase model for 35B Python tokens, resulting in a new model that we call StarCoder. We found that StarCoderBase outperforms existing open Code LLMs on popular programming benchmarks and matches or surpasses closed models such as code-cushman-001 from OpenAI (the original Codex model that powered early versions of GitHub Copilot). With a context length of over 8,000 tokens, the StarCoder models can process more input than any other open LLM, enabling a wide range of interesting applications. For example, by prompting the StarCoder models with a series of dialogues, we enabled them to act as a technical assistant.