In the early days of computing, programmers wrote code entirely on their own, from scratch and solo. Hardcore mode! The only help they had was paper reference books describing the syntax of specific languages.
Today, things are very different. In addition to countless electronic manuals, guides, articles, videos, and forums, we now have neural networks, arguably one of the most groundbreaking technologies of the early 21st century.
Trained on massive datasets, these AI models have become the primary source of coding assistance.
The advantages are obvious. AI coding tools speed up the development process by taking on much of the routine work involved in writing code. This allows developers to focus on architecture and logic instead of syntax errors and inefficient constructs.
Some tools generate code from scratch, and others analyze and complete already-written code.
However, in recent years, so many AI-powered projects have emerged that it can be difficult for the average person to figure out which AI is actually the best for programming.
There are both specialized and general-purpose models. Some only generate specific types of data (like code), while others handle all kinds (text, code, images). Some are free, others paid.
To determine which AI is the best for programming (and why), we first need to create a list of the top coding AIs, and then analyze the pros and cons of each one.
Copilot is arguably the best AI coding assistant, developed by GitHub in collaboration with OpenAI. It’s positioned as an AI co-programmer trained on millions of open-source GitHub repositories.
Developed by the largest cloud-based code hosting platform, Copilot leads the list of neural networks for programming, offering a wide range of capabilities:
Code Generation: Produces ready-to-use code snippets in all major languages based on text descriptions: scripts, functions, classes, even entire files. While the AI sometimes generates imperfect results, this can be resolved by making the user’s request more specific.
Code Translation: Converts code written in one programming language into logically equivalent code in another. This feature alone puts Copilot ahead of many other coding AIs, as not all models can do this effectively.
Code Autocompletion: Suggests autocompletion based on the overall context of the codebase.
Refactoring: Enhances code structure, optimizes algorithms, and fixes errors. It can also suggest alternative, more efficient solutions that a developer might not have initially considered.
Editor Integration: Integrates via plugins into popular text editors and IDEs like Visual Studio Code, Neovim, JetBrains IDEs, and others.
These features help automate routine coding tasks.
A lesser-known use case of Copilot is learning programming languages. The AI can generate simple code snippets that demonstrate the syntax and mechanics of a specific language.
Interestingly, this teaching method aligns with Stephen Krashen’s Comprehensible Input Hypothesis, which states that language acquisition is driven by understandable input, i.e., the material that the learner can interpret with explanation.
Similarly, Copilot can be used as an interactive reference, potentially replacing resources like Stack Overflow.
Copilot supports all major programming languages: C, C++, C#, Go, Java, JavaScript, Kotlin, PHP, Python, Ruby, Rust, Scala, Swift, and TypeScript.
It can also generate code using popular frameworks and libraries like React, Angular, Vue.js, Node.js, Django, Flask, and Ruby on Rails.
Naturally, GitHub offers only a limited set of Copilot features for free. The free version also has monthly limits on code generations.
The full version is available through subscriptions for individuals, teams, and enterprises. Pricing starts at $4/month, with a 30-day free trial. In return, users get a powerful tool for faster coding.
Despite requiring a subscription, many developers consider Copilot the best AI coding assistant, especially when compared to general-purpose models like ChatGPT, which aren't primarily designed for code generation.
Tabnine is an AI that generates code snippets not based on explicit prompts but on the development context formed by the programmer’s current work.
Unlike Copilot, Tabnine primarily focuses on code autocompletion. However, it also offers several distinctive features:
Offline Mode: The Enterprise version of Tabnine can run entirely offline, generating code without internet access. This improves data privacy, as code is processed locally and not sent to the cloud; however, it does require more system resources.
Personalized Generation: Tabnine learns from a specific developer’s codebase, mimicking their unique style and preferences. This results in personalized suggestions that feel as if the code were written by the developers themselves, in contrast to Copilot, which was trained on public GitHub repositories.
IDE Integration: Since Tabnine is not a standalone application but a smart autocompletion engine, it integrates with virtually all major IDEs through plugins, including VS Code, IntelliJ, Visual Studio, Eclipse, Android Studio, AppCode, CLion, GoLand, Neovim, PhpStorm, PyCharm, Rider, RubyMine, WebStorm.
Interactive AI Chat: Tabnine also offers a built-in chat interface for personalized communication with the AI. Users can ask questions related to the code in their current editor tab.
All in all, Tabnine is geared more toward typing speed and efficiency rather than generating large chunks of code from scratch. Think of it as classic autocompletion but supercharged with AI.
Like Copilot, Tabnine supports autocompletion for all major programming languages: Python, JavaScript, TypeScript, Java, C/C++, C#, Go, Ruby, Swift, PHP, Rust, Kotlin, Perl, Dart, Scala.
Tabnine is available under two subscription plans:
The Enterprise plan offers advanced customization options, enhanced security, and on-premise deployment for maximum privacy.
ChatGPT is a generative AI developed by OpenAI, based on the GPT (Generative Pre-trained Transformer) architecture.
Unlike Copilot and Tabnine, ChatGPT can generate not just code but also various forms of text content. That makes it a general-purpose neural network—a versatile tool for generating any data based on a user's prompt.
Some might argue that ChatGPT is more text-oriented than code-focused. However, it remains one of the best free AI for coding, as its basic version is available to everyone without a paid subscription.
ChatGPT operates through a chat interface, where prompts are entered as natural language messages.
That’s why its name consists of Chat and GPT:
In short, ChatGPT is a conversational AI capable of tackling almost any language-based task — including code generation.
Here’s what it can do:
Conversational Interaction: The AI responds as if you were chatting with another person. You can ask it to use a certain tone, generate text, tables, code, and even simple images. This makes ChatGPT a virtual assistant, coworker, or advisor.
Free Code Generation: The base model is completely free to use. More advanced versions offer improved performance but require a subscription.
Multi-Format Output: It can create more than just code. You can generate any language-based content based on a clear prompt and adapt it to the ongoing context of the conversation.
For example, you could write this fun prompt:
“Give me an example of Python code with a helicopter and a car class. Each should have a fuel variable initialized to 100. Then create objects of each class and have the helicopter hook the car with a cable.”
ChatGPT would generate something like this:
class Helicopter:
def __init__(self):
self.fuel = 100
self.hooked_car = None
def hook_car(self, car):
self.hooked_car = car
print("The helicopter has hooked the car with a cable.")
class Car:
def __init__(self):
self.fuel = 100
helicopter = Helicopter()
car = Car()
helicopter.hook_car(car)
You can check this code in any online Python interpreter and get the expected output:
The helicopter has hooked the car with a cable.
So, if you're working late at night and wondering which neural network is best for hands-off code generation, ChatGPT is worth considering. After all, OpenAI is a global leader in machine learning.
At the very least, ChatGPT is the best conversational AI for code creation, capable of generating not only code but also full documents, tables, and even basic images.
Since it was trained on a vast linguistic dataset, ChatGPT can generate code in nearly any language and not just general-purpose ones.
It supports all major programming languages, including Python, JavaScript, TypeScript, Java, C, C++, C#, Go, PHP, Swift, Kotlin, Ruby, Rust, Haskell, Lisp, Elixir, Erlang, and F#.
It also understands domain-specific languages: HTML, CSS, SASS/SCSS, SQL, GraphQL, Shell, PowerShell, Lua, Perl, YAML, and JSON.
Listing them all would be pointless, as ChatGPT can understand and generate code or text in virtually any format. That's its defining strength.
OpenAI offers four subscription tiers for ChatGPT, each expanding the capabilities of the last:
Paid plans provide higher accuracy, better performance, and more stability. Still, the free version offers nearly identical functionality — the difference lies in the fine details.
Claude is another natural language processing AI developed by Anthropic. According to its creators, Claude is a safer, more ethical, and more predictable alternative to ChatGPT.
Overall, Claude's capabilities are similar to ChatGPT’s, with a few notable distinctions:
Image and Document Analysis: Claude can interpret the contents of images and documents in detail, recognizing real-world objects, diagrams, graphs, numbers, and text. ChatGPT is also capable of this, but only in its paid version. Claude offers it natively.
Massive Context Window: Claude supports up to 200,000 tokens, which allows it to analyze large volumes of data. By comparison, ChatGPT maxes out at around 128,000 tokens. One token is roughly 5 characters of English text.
High Ethical Standards: Thanks to built-in ethical constraints, Claude is less likely to generate inappropriate content, making its responses more conservative. While this may not matter to some users, from a broader perspective, output filtering is a key trait that separates the best AI coding tools from the rest, especially as AI tools become mainstream.
In short, Claude offers high factual accuracy, which is crucial for generating reliable code based on user instructions.
According to Anthropic, Claude performs best when generating Python code. However, it also supports other popular languages: JavaScript, Java, C++, Go, PHP, Ruby, C#, Swift, TypeScript, Kotlin, and Rust.
Of course, the full list of supported languages isn’t publicly available, as the model was trained on diverse datasets. Practical testing is the best way to determine support.
Claude offers several pricing tiers:
Despite Claude being one of the top free AI for coding, it can’t be considered a full competitor to ChatGPT.
Here’s why:
Still, Claude is worth trying for anyone who regularly uses AI in programming or text generation tasks.
Snyk Code is an AI-powered static analysis tool for detecting vulnerabilities and errors, part of the broader Snyk ecosystem.
Trained on a database of known vulnerabilities (updated regularly), Snyk Code focuses on secure development:
Vulnerability Detection: Performs real-time code analysis during development and commits to catch threats before they reach production.
Development Tool Integration: Works with GitHub, GitLab, Bitbucket, and Azure Repos, and is compatible with popular IDEs: VS Code, IntelliJ IDEA, PyCharm, WebStorm, Eclipse.
Contextual Fix Recommendations: For every issue found, it provides an explanation and sample fixes, helping developers patch their code quickly and securely.
In essence, Snyk Code is best used after you have written the code as an added security layer before deployment.
Snyk Code supports major programming languages only: Apex, C, C++, Go, Groovy, Java, Kotlin, JavaScript, .NET, PHP, Python, Ruby, Scala, Swift, Objective-C, TypeScript, VB.NET.
Snyk Code is free for individual use, but teams and companies can choose from the following:
While Snyk Code doesn’t generate code, its powerful analysis tools and free tier perfectly justify its inclusion in any list of the best free AI tools for coding.
Documatic is an AI that automatically generates documentation and enables codebase exploration. It analyzes the project, extracts key information, and structures it for easy reference.
Documatic is designed for codebase analysis; all other functionality stems from this core:
Automatic Documentation Generation: Produces detailed code explanations, reducing the need for manual comments.
Code Search and Navigation: Responds to developer queries with relevant code snippets and context.
Project Structure Visualization: Displays project components (dependencies, microservices, repos) as interactive graph nodes, useful for understanding complex architectures.
Code Explanation: Clarifies algorithms and logic, making unfamiliar projects easier to understand.
Documatic is passive: it doesn’t generate code, only analyzes and documents it.
It supports modern interpreted and compiled languages: Python, Java, JavaScript, TypeScript, Go, C#, PHP.
Documatic keeps things simple with just two tiers:
While it’s easy to chase the best AI coding tools, it’s crucial to remember: the developer matters more than the AI. Skills, logic, creativity, and experience outweigh any neural network’s output.
You should only upgrade to premium tools when free features no longer meet your needs.
Mintlify is a comprehensive online platform for automating code documentation with AI.
Unlike Documatic, Mintlify offers cloud hosting with visually styled, user-accessible documentation sites.
For instance, a developer or team building a JavaScript library can generate full documentation from a GitHub repo, resulting in a live, multi-page site with API references. These pages are editable using a WYSIWYG editor.
Fun fact: Anthropic uses Mintlify to power the documentation for Claude.
Mintlify connects the project’s codebase to a public-facing documentation site, offering:
Automated Documentation Generation: Generates detailed documentation (including API references) directly from your codebase.
Version Control Integration: Syncs with GitHub and GitLab, ensuring documentation updates automatically when the code changes, which makes it perfect for CI/CD pipelines.
Documentation Site Hosting: Creates a stylish, SEO-optimized site with editable sections.
Analytics & Feedback: Provides user analytics and supports direct feedback collection to improve documentation quality.
While powerful, Mintlify has a learning curve as its feature-rich interface takes time to master.
Supports 12 modern languages: Python, JavaScript, TypeScript, C, C++, PHP, Java, C#, Ruby, Rust, Dart, Go.
Mintlify offers four plans:
Where other AI coding tools show their intelligence directly, Mintlify’s AI works silently in the background.
At first glance, it may seem like a manual documentation editor; however, over time, it reveals itself as an automation powerhouse, seamlessly connecting code to documentation.
Codeium is an AI-powered coding assistant that consists of several products built on artificial intelligence:
In addition to these, there’s a browser-based chat called Live, as well as numerous IDE extensions – Codeium Extensions.
The Codeium Windsurf Editor integrated development environment, with the code editor on the left and the AI chat on the right. Source: codioailab.com
Codeium offers a wide range of features that assist during coding and code editing:
Code Autocompletion: Provides intelligent suggestions as you type.
Chat Assistant: A built-in AI chat can explain code snippets in detail, offer refactoring suggestions (passively while you write), and answer programming questions directly within the development environment. It can also advise on build commands and configuration.
Intelligent Search: Ensures quick access to classes, methods, functions, and code fragments, streamlining navigation in large codebases.
Essentially, Codeium aims to provide a comprehensive suite of tools for virtually all coding scenarios – all powered by AI.
Supports all popular programming languages, including: Python, JavaScript, TypeScript, Go, Java, C#, PHP, Ruby, Kotlin, Swift.
Codeium offers several pricing plans for both individual developers and entire teams:
Gemini is a versatile AI developed by Google. Despite being relatively new, it rounds out our list of the top AI coding assistants in 2025. Unsurprisingly, it’s a direct competitor to both ChatGPT and Claude.
It’s important to recognize that Google is a major player (arguably a monopolist) in the software market. With vast cloud infrastructure, massive data resources, and many popular services (plus its own OS, Android), Gemini offers a broad array of capabilities for working with both text and visual data:
Text Generation, Analysis, and Translation.
Image Generation and Analysis: Generates images from text prompts and can also analyze images and describe their contents.
Code Generation and Analysis: Generates code snippets in any language and format. Also understands and analyzes code, providing suggestions for improvement. Google also offers the Gemini Code Assist extension for popular IDEs.
Integration with Google Services: Integrated with many Google apps and Android tools.
Fast Response Generation: Provides answers faster than ChatGPT and generally operates at a higher speed.
Large Context Window: Can handle up to 1 million tokens.
Notably, the advanced capabilities of Gemini’s language model are available through a special AI Studio for developers. This environment allows not only text-based interaction but also screen sharing for more detailed feedback.
AI Studio is designed for app developers who want to test Gemini integration with their products.
Gemini supports the following major programming languages: Python, Java, C++, JavaScript, Go, TypeScript, C#, Ruby, PHP, Swift, Kotlin, Rust, SQL, HTML, CSS, Bash, Perl, Lua, R, Dart, Scala, Julia, Fortran.
Google offers a fairly straightforward pricing structure for Gemini:
Thus, just like ChatGPT, Gemini is another great free AI for programming, particularly when it comes to working with general-purpose data. The ability to generate not only code but also supporting text is an important asset in development.
So, what is the best AI for coding? That’s for each user to decide. Some may be satisfied with intelligent autocompletion, while others may require the generation of large code fragments across multiple languages – complete with detailed explanations.
Model |
Type |
Features |
Pricing |
Copilot |
Specialized |
Code generation, autocompletion |
Subscription |
Tabnine |
Specialized |
Autocompletion |
Subscription |
ChatGPT |
General |
Generation, analysis |
Free, subscription |
Claude |
General |
Generation, analysis |
Free, subscription |
Snyk Code |
Specialized |
Analysis |
Free, subscription |
Documatic |
Specialized |
Documentation |
Free, subscription |
Mintlify |
Specialized |
Documentation, hosting |
Free, subscription |
Codeium |
Specialized |
Generation, analysis |
Free, subscription |
Gemini |
General |
Generation, analysis |
Free, subscription |
Ultimately, the most important factor is not the tool itself, but the developer using it. Skills, experience, logic, critical thinking, and creativity all outweigh the capabilities of any neural network.
So, switching to paid versions of AI products – whether they’re code generators or analyzers – only makes sense when the free version clearly falls short for your needs.