Github Copilot Alternatives

Top 12 Github Copilot Alternatives in 2024

Github Copilot, launched in 2021, set a new standard for AI pair programmers. Its code suggestions saves developers hours of work. However, as great as Copilot is, developers have many alternatives in 2024. These GitHub Copilot competitors offer unique capabilities.

Key Factors to Consider When Choosing an Alternative

When evaluating the GitHub Copilot alternatives, here are some key factors developers should consider:

  • Open source: Can the model powering the tool be audited?
  • Code suggestion capability: How effectively does it autocomplete code?
  • Multi language support: Number of languages supported.
  • Accuracy: Percentage of correct code suggestions.
  • Responsiveness: Latency in showing code suggestions.
  • IDE integration: Availability as editor plugins.
  • Pricing: Free or paid plans offered.

OpenAI Codex

OpenAI Codex is one of the top GitHub Copilot alternatives. Launched in 2021 alongside Copilot, Codex focuses more on natural language than code. It translates text to code in over a dozen languages. The AI understands much more context than Copilot.

While Copilot generates code line-by-line, Codex produces whole functions or programs. This makes it better for vague prompts. It even handles typos and poorly worded questions. Codex does lack Copilot’s programmer-specific training though.


Tabnine utilizes a powerful AI code completion tool. It integrates directly into most popular IDEs. The completions require only a few characters to activate. This allows coding with minimal interruption.

Tabnine’s training focuses on production code. It gives highly relevant suggestions for real-world tasks. The suggestions avoid obscure code conventions too. This makes it easier for others to understand the code later.


Kite offers Copilot-style completions like Tabnine. But it also adds extensive code documentation. The tooltips detail method arguments, exceptions, and more. Kite even shows how popular each method is among developers.

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Kite really shines for Python coders. It has deep insight into Python’s massive ecosystem. This allows intelligent autocompletion even for obscure modules. Kite supports many other languages too though.


CodeWhisperer combines GitHub Copilot strengths with a visual interface. The AI suggestions appear in editable boxes inside the code editor. Developers can easily accept, edit, or reject them as needed.

CodeWhisperer also simplifies launching. The web app requires no installation whatsoever. Plus, it integrates with over a dozen major code editors. CodeWhisperer offers a more guided Copilot experience.

Tabnine Autocomplete

Tabnine Autocomplete builds upon the original Tabnine tool. It specifically targets intelligent code completion with fewer keystrokes. For typing “std”, it may suggest “std::vector” or “std::cout” appropriately.

Like Copilot, Tabnine Autocomplete adapts to your code. It gives better suggestions in later sessions upon seeing more examples. The tool also integrates with all IDEs through language servers or plugins.

GitHub Arctic Code Vault

GitHub Arctic Code Vault preserves open source code for future AI training. Copilot-style tools require massive datasets across languages and years. Arctic Code Vault creates this treasury of examples.

The project stores GitHub repositories on film reels inside an Arctic vault. This protects the data from disasters like fires. Future AIs may one day reference this archive just as we reference ancient libraries today.

AI Coding Assistant

AI Coding Assistant combines Copilot-style autocomplete with visual tools. Its interface shows variable values live as you code. The assistant also visualizes program architecture plans. These features help developers stay organized.

For autocompletion, AI Coding Assistant favors simple code over complex code. This produces cleaner and more maintainable programs. The tool currently supports Java, Python, JavaScript, TypeScript and SQL code.


DeepCoding utilizes GPT-3 for code generation. This complex AI handles more ambiguous prompts than Copilot training. It produces quality code even from conceptual descriptions written in plain English.

DeepCoding also simplifies launching through its browser-based interface. The visual tools allow editing suggestions or regenerating code easily. Overall, DeepCoding generates fuller programs compared to Copilot’s line-by-line hints.

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AI Code Completion

AI Code Completion offers text autocompletion with AI support. It focuses on writing natural language, not code. The tool handles documents, emails, essays, and more. For developers writing documentation, it saves significant time.

The assistant trained on millions of webpages and books. It learns proper grammar, style conventions, and topics. AI Code Completion reduces typos and mistakes in long-form writing. The tool currently supports English, French and Spanish.


LuisAI provides an AI assistant for coding in Python or JavaScript. Developers can describe app requirements in plain English. LuisAI handles translating concepts into full code right inside a Docker container.

This tool especially accelerates prototyping projects. LuisAI reduces the need to lookup syntax for realizing concepts. It also automatically handles imports, validations, error handling boilerplate code too.

AI Programming Assistant

AI Programming Assistant focuses specifically on Python and web development. It generates full code from English descriptions like “create login form”. The assistant handles database schemas, CRUD APIs, front-end code and more.

This tool particularly helps new developers learn conventions faster. It handles tedious syntax details automatically after describing the logic. AI Programming Assistant also explains its code to reinforce learning.


Claude offers a general assistant for working professionals. While not specifically coding-focused, it answers questions, analyzes data, writes content and more. Claude simplifies knowledge work, allowing focusing time on specialized program logic.

The assistant handles related tasks like managing schedules, research, bookkeeping and documentation. Developers can query Claude for feedback on work-in-progress too. For common workplace needs outside of coding, Claude is ideal.


GitHub Copilot set a high benchmark for AI pair programmers in 2021. While fantastic, many alternatives now meet or exceed Copilot’s capabilities in specific areas. Codex interprets broader prompts with its vast language model. Tools like Tabnine and Kite optimize for fast autocompletion within IDEs. And new offerings like CodeWhisperer and DeepCoding simplify utilizing AI-generated code.

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As AI assistants focus on different strengths, the future likely holds an ecosystem of coding tools rather than one solution for all needs. Developers in 2024 have an expanding set of Copilot alternatives to boost their productivity.


Which GitHub Copilot alternative is best overall?

AThere is no single “best” alternative, as each tool has strengths for different cases. Codex excels at conceptual prompts, Tabnine is fastest in IDEs, CodeWhisperer simplifies interactivity, etc. Most developers utilize a combination based on their needs.

Do these AI coding assistants replace developers?

No, they just augment human developers. Their code suggestions still require review, testing and integration. And developers direct the tools by establishing project parameters. AIs handle tedious syntax challenges but don’t set strategy.

How is the code from AI tools licensed?

Most alternate licenses generated code under MIT, allowing modification and redistribution. But check each tool as some require attribution or limit liability around potential defects. Usage within proprietary software is generally permitted.

Why consider alternatives when GitHub Copilot already exists?

Copilot pioneered several concepts but had limitations around interpretability, context-handling and output control. Many alternatives now surpass it in key areas while benefiting from public benchmarking. Healthy competition drives innovation.

Will AI take away coding jobs in the future?

Unlikely as pure coding is a small part of most developer roles. Architecting solutions, communicating with others and optimizing business needs will still require people. AI assistants handle the tedious syntax challenges.