7 Best AI Coding Assistants to Try in 2025

ChatGPT and GitHub Copilot have made significant waves in the programming community. CodeSignal estimated that 81% of developers now utilize AI-powered coding assistants – almost double the percentage reported in Stack Overflow’s 2023 Developer Survey conducted just six months prior.

Whether you’re a student, a novice developer, or a seasoned professional, there’s an AI coding assistant available to support your programming journey, with options catering to all skill levels and budgets.

But what exactly is an AI coding assistant, and why should you consider using one? With so many choices on the market, selecting the right tool can feel daunting.

In this blog, we will delve into the 7 best AI coding assistants, emphasizing their unique features, capabilities, and pricing, among other important factors.

Let’s get started!

What Is an AI Coding Assistant?

An AI coding assistant is an advanced software tool that assists developers in numerous programming tasks. These tools can analyze code snippets, offer helpful suggestions, spot errors, and even generate complete code blocks based on user inputs.

Typically found within integrated development environments (IDEs) or available as standalone applications, they support a variety of programming languages.

Three well-known AI coding assistants include GitHub Copilot, Tabnine, and Microsoft IntelliCode.

These coding tools leverage large language models (LLMs) that have been trained on extensive datasets comprising code from various sources, such as open-source projects, programming language documentation, and tutorials.

The wider the selection of code they have learned from, the better their understanding and accuracy become. This broad exposure enables them to recognize patterns, recommend code snippets, and tackle complex programming challenges effectively.

Also read: 9 Best AI Tools for Business to Boost Productivity

Pros and Cons of Using AI Coding Assistant Tools

AI programming tools are gaining popularity for their ability to drive productivity and streamline workflows. However, it’s important to recognize both their benefits and drawbacks.

Pros	Cons
Increased efficiency: AI coding tools help developers accelerate their work by automating repetitive coding tasks. This allows them to dedicate more time to the creative and complex elements of programming while the AI manages routine code generation.	Risk of over-reliance: Relying too much on AI can be problematic. If developers depend on AI for coding recommendations without fully grasping the underlying logic, it may hinder their growth and ability to solve problems independently. This dependence can prevent the development of strong coding skills.
Error detection and debugging support: AI coding tools are capable of spotting errors in code lines. With real-time error detection, these tools enable programmers to identify mistakes early on, saving them valuable time in the debugging process.	Security and privacy issues: Many AI coding applications operate on cloud platforms, which can raise concerns about the safety and privacy of shared code. Sensitive information might be at risk, leading to potential data breaches or security vulnerabilities. Developers should exercise caution, particularly when dealing with confidential or proprietary code.
Access to learning resources: AI coding assistants offer useful learning materials by providing suggestions, examples, and explanations. For beginners, these tools can serve as virtual tutors, guiding them through best practices. Even experienced developers can benefit by discovering new techniques and staying current with programming trends.	Limited contextual understanding: While AI coding tools are powerful, they often lack the deep understanding needed for complex or context-specific challenges. They may perform well with standard coding tasks but might provide inaccurate or irrelevant suggestions for projects with unique requirements. developers may need to modify or discard AI-generated code that doesn’t fit their overall project goals.

Top 7 AI Coding Assistant Tools

There are many excellent options available for AI coding assistants. Here’s a look at the seven best AI coding assistants worth considering in 2025.

1. GitHub Copilot

GitHub Copilot, developed by GitHub and OpenAI, is a popular AI code completion tool that excels in generating code right as you type. It integrates seamlessly with code editors like Visual Studio Code, GitHub Codespaces, JetBrains IDEs, and Neovim, offering real-time suggestions based on the context of your code.

Key features:

• Code suggestions: Complete lines or entire functions based on your code and comments.

• Chat functionality: An in-editor chatbot provides answers to coding questions, debugging assistance, and more.

• Auto-complete navigation: Easily cycle through multiple suggestions to find the best fit for your code.

• Wide compatibility: Work with various IDEs, like Visual Studio, Neovim, Visual Studio Code, and JetBrains, along with diverse programming languages, including TypeScript, Golang, Python, and JavaScript.

Pricing:

Free for individuals; team pricing starts at $4 per month per user.

2. Neurond Assistant

Neurond Assistant is a versatile AI-powered coding and productivity tool that customizes its support to fit each user’s preferences and skills. It provides personalized code suggestions, document interactions, and data analysis across multiple programming languages and file types. On top of that, the assistant leverages advanced AI models to deliver accurate and context-aware assistance.

Key features:

• Code generation: Provide contextually relevant code suggestions and completions based on user preferences and project requirements.

• User memory: Personalize responses by remembering individual user details, including programming language preferences and professional background.

• Artifacts: Create interactive, standalone content windows for numerous tasks, such as coding, web development, data visualization, and graphic design.

• Document chatting: Process and analyze various file types (Excel, CSV, PDF, Word, Text, Markdown), offering summaries and enabling in-depth information retrieval.

• Multi-model integration: Harness the power of the latest AI models, including GPT-4, GPT-4 mini, Gemini 1.5 Flash, Gemini 1.5 Pro, Claude 3, and Claude 3.5 Sonnet for diverse capabilities.

Pricing:

Currently, Neurond Assistant is not available for public use. It is exclusively provided to internal staff at no cost. This restricted access ensures a controlled environment for testing and refinement, potentially leading to a more polished product when it becomes publicly available.

3. Tabnine

Tabnine is an AI-powered, privacy-centered code generation tool that boosts code quality and coding speed. With support for over 80 programming languages and major IDEs, it gives intelligent, context-aware code suggestions.

Tabnine’s flexibility offers both local and cloud-based models, making it suitable for developers with privacy concerns or specific project needs.

Key features:

• Code refactoring assistance: Offer guidance and suggestions for refactoring code to improve readability, efficiency, and maintainability.

• Code linting: Highlight and suggest fixes for potential errors, helping maintain clean, error-free code.

• Automated code documentation: Automatically generate documentation, making collaboration and code understanding easier.

• Intelligent code completions: Deliver relevant code completions from a dataset of open-source code for accurate, context-aware suggestions.

• Local and cloud models: There are multiple options, with cloud-based models using Tabnine’s large AI dataset, while local models allow work to stay on the developer’s machine—ideal for sensitive or proprietary projects.

• Team-level AI models: Provide team-trained models that adapt to a team’s coding standards, patterns, and frameworks.

Pricing:

Tabnine offers a free Starter plan for basic AI code completions, with paid plans beginning at $12 per month per user.

4. IntelliCode

Microsoft IntelliCode is an AI-driven code completion tool built into Visual Studio and Visual Studio Code that helps developers write code faster and more efficiently through intelligent code suggestions.

IntelliCode understands your code’s context and style by using machine learning models trained on thousands of GitHub projects, delivering highly relevant suggestions.

Key features:

• Autocompletion: Provide whole-line autocompletion based on code context, helping speed up the development process.

• Enhanced privacy: Run locally on your device, ensuring code privacy while providing precise, context-aware suggestions.

• Contextual IntelliSense: Rank the most relevant suggestions at the top by analyzing thousands of open-source projects.

• Repeated edits detection: Detect repetitive edits and allow you to apply changes consistently across the codebase.

• Quick actions: Identify common coding patterns and suggest quick actions to simplify tasks, such as generating constructors and adding parameters.

Pricing:

IntelliCode is available for free with Visual Studio and Visual Studio Code.

5. Amazon Q Developer

Amazon Q Developer is a cutting-edge code generator powered by machine learning that suggests real-time codes directly in your IDE. Trained on a vast dataset of open-source code, it can recommend anything from small snippets to complete functions based on comments and existing code.

This tool supports multiple programming languages and is compatible with several IDEs, including JetBrains IDEs, Visual Studio Code, and AWS Cloud9.

By automating repetitive tasks, Amazon Q Developer elevates productivity and helps create precise, secure code according to the latest industry standards. It’s an excellent resource for developers looking to work more efficiently and accurately.

Key features:

• Code suggestions: Provide tailored snippets, functions, and even entire classes based on contextual cues in the code, saving time and reducing errors.

• Function completion: Suggest subsequent lines and can even complete entire function bodies, simplifying the coding process.

• Documentation generation: Automatically create detailed documentation, including function summaries, parameter explanations, and return values.

• Security scanning: Proactively detect potential security vulnerabilities, allowing developers to address issues before they arise.

• Language and IDE integration: Work with a wide range of programming languages, including Python, JavaScript, C#, Rust, PHP, Kotlin, and SQL, ensuring broad compatibility.

• IDE integration: Easily integrate with popular IDEs like JetBrains and VS Code for improved usability.

Pricing:

Individuals can access Amazon Q Developer for free, with a professional plan available starting at $19 per month.

6. Replit

Replit is another intelligent AI code generation tool that is known for its advanced in-line suggestions, mistake detection, and interactive learning environment. This tool empowers developers to generate code faster, learn effectively, and produce high-quality results.

Key features:

• Advanced in-line suggestions: Provide smart suggestions that help developers code more efficiently.

• Code explanation and comments: Offer explanations and comments for code snippets, helping developers understand and document their work effectively.

• Mistake detection and correction: Identify errors in code and offer guidance for corrections, ensuring accuracy and reducing mistakes.

• Interactive learning environment: Allow developers to learn coding in context, creating an immersive and educational experience.

Pricing:

Replit is free for individual users, with optional subscription plans available, including the Hacker plan at $7 per month and the Pro plan at $20 per month.

7. DeepCode AI

DeepCode AI, developed by Snyk, is a powerful AI coding assistant that improves software security and developer productivity.

Unlike many other AI coding tools, DeepCode AI employs a hybrid approach, using symbolic AI, generative AI, and machine learning models trained on extensive security-specific data gathered by top researchers.

Key features:

• Hybrid AI: Combine different AI models to reduce errors and improve accuracy, minimizing common issues associated with AI-generated suggestions.

• AI-powered quick fixes: Provide in-line quick fixes while automatically scanning to make sure they don’t create new problems, boasting an average success rate of 80%.

• Customized rule creation: Allow users to write queries with autocomplete functionality, making it easier to create and manage custom rules.

• CodeReduce Technology: Optimize processing time and the amount of code the LLMs need to handle, increasing the quality of fixes and reducing inaccuracies.

Pricing:

DeepCode AI is available through Snyk’s security platform. Features are accessible in Snyk’s free plan or through paid subscriptions starting at $25 per month for teams.

How to Choose the Best AI Coding Assistant?

Selecting the right AI coding assistant plays a critical role in bolstering your daily development workflow and team collaboration. While many options provide similar core features, their unique implementations, specializations, and integration capabilities may differ.

Here are 5 key factors to consider when evaluating AI coding assistants:

• Code privacy and security: Prioritize how the tool manages your proprietary code. Look for assistants that provide clear data retention policies and local processing options and adhere to your organization’s security standards.
• Integration capabilities: Ensure the assistant seamlessly integrates with your current development environment and supports your technology stack. It should work well with your preferred integrated development environments and version control systems and accommodate all programming languages and frameworks used by your team.

• Model Quality and Training: The AI models should be trained on high-quality, relevant codebases and regularly updated to reflect new programming trends and best practices. The tool’s suggestions should align with modern development practices and language-specific conventions.

• Customization and learning: Look for an assistant that can adapt to your team’s coding style and preferences, providing increasingly relevant suggestions over time. Consider whether it can learn from your codebase and allow for custom rules and style configurations.

• Cost and scalability: Evaluate the pricing structure to confirm it fits your team size and usage needs, with room for future growth. Weigh the long-term costs against potential productivity gains, considering whether the licensing model can support your team’s expansion.

Conclusion

There you have it – the top 7 AI coding assistants to explore in 2025, each offering distinct features for developers of all experience levels, with both free and paid options available.

From GitHub Copilot’s in-depth suggestions to Amazon CodeWhisperer’s seamless AWS integration and Tabnine’s open-source training approach, there’s an AI assistant to suit every preference and project need. These tools are designed to boost productivity and efficiency, but remember, they’re here to support—not replace—human creativity and problem-solving. The best developers will use these assistants to streamline repetitive tasks, dedicating their focus to high-level design and innovation.

At Neurond, we offer Neurond Assistant as a high-quality coding assistant—completely free—as well as a suite of advanced AI solutions, including machine learning, natural language processing, computer vision, recommendation systems, and many more.

Reach out to us now, and let us guide you through the next steps to boost your development capabilities.