Every coder’s workflow now has a co-pilot, quite literally. In the ongoing dialogue of JetBrains AI Assistant vs Copilot, both tools have emerged as powerhouse contenders among AI code generation tools and AI software development assistants.
These platforms promise a smarter AI assistant for developers, from instant code suggestions to context-aware refactoring. And the reasons for their popularity are clear: a staggering 84% of developers reported using AI tools in their workflows, with over half relying on them daily, according to Stack Overflow’s survey.
In this article, we will break down the difference between JetBrains AI Assistant and Copilot across five key dimensions, examining everything from their pricing and standout features to their strengths and weaknesses.
Key Takeaways
- JetBrains AI Assistant integrates deeply with JetBrains IDEs, while Copilot works across multiple platforms.
- JetBrains focuses on code refactoring and explanations, while Copilot excels at code generation.
- Copilot has flat monthly pricing while JetBrains pricing ties into IDE subscriptions.
- JetBrains emphasises local control and compliance, while Copilot relies on cloud processing.
What is JetBrains AI Assistant?
JetBrains AI Assistant is an AI-powered coding tool built into JetBrains IDEs like IntelliJ IDEA, PyCharm, and WebStorm, designed to help developers with tasks such as code explanations, intelligent refactoring, test generation, and in-IDE chat.
Unlike general-purpose tools, it leverages the deep project context within JetBrains environments, making it a tailored AI assistant for developers who prefer JetBrains products.
It seamlessly “weaves AI assistance into the core IDE user workflows,” offering highly contextual support to help developers write, understand, and improve code more efficiently.
Key Features of JetBrains AI Assistant
JetBrains AI Assistant brings a suite of intelligent AI coding tools directly into JetBrains IDEs, designed to streamline development.
From smarter navigation to automated code improvements, it enhances both productivity and code quality.
| Feature Category | Description |
|---|---|
| AI Chat | Natural-language interaction for code-related queries and iterative prompts in multiple IDEs. |
| Code Completion | Smart, context-aware suggestions for lines, functions, or blocks, enhanced by Mellum and other LLMs |
| Code Explanation & Queries | Explains code, runtime errors, SQL queries, regex, commit logic, and more in plain language. |
| Code Generation | Automatically produces code snippets, commit messages, documentation, tests, terminal commands, and translations. |
| Refactoring & Naming Suggestions | Offers context-aware refactoring and naming ideas, enhancing readability and maintainability. |
| Prompt Library (Quick Actions) | Access and use prewritten prompts or create your own, directly from the editor. |
| Language & IDE Coverage | Compatible with most JetBrains IDEs (e.g. CLion, DataGrip, WebStorm, etc.) and also available as a VS Code plugin. |
| Model Flexibility | Uses multiple language models, including OpenAI, Google Gemini, and JetBrains’ own Mellum and supports both cloud and local LLMs |
| Agentic Mode | Orchestrates multiple models collaboratively under developer supervision for complex tasks, especially in VS Code |
| Telemetry & Privacy Control | Offers licensing transparency, optional telemetry, and robust privacy settings tailored for compliance and enterprise usage |
JetBrains AI Assistant Pricing Overview
JetBrains AI Assistant offers flexible licensing tiers to match varying developer needs and usage levels.
Each tier includes the same core AI features, such as unlimited code completion, in-IDE AI chat, refactoring, test generation, and access to both cloud and local LLMs, but the difference lies in how many AI Credits (used for cloud-dependent features like Junie and chat) you receive each.
| License Tier | Price | Monthly AI-Credit Quota |
|---|---|---|
| AI Free | $0 (Free) | 3 AI Credits per month |
| AI Pro | $100 per year | 10 AI Credits per month |
| AI Ultimate | $300 per year | 35 AI Credits per month |
| AI Enterprise | $720 per year | The maximum number of credits, enterprise security, and custom AI integrations. |
Pros and Cons of JetBrains AI Assistant
Like any AI coding tool, JetBrains AI Assistant has its strengths and limitations. Understanding them helps developers decide if it fits their workflow and long-term needs.
| Pros | Cons |
|---|---|
| Deep integration with JetBrains IDEs, offering project-aware suggestions. | Limited to JetBrains IDE users (no standalone usage outside the ecosystem). |
| Strong code explanations, refactoring, and documentation capabilities. | Learning curve for developers unfamiliar with JetBrains’ AI Credit system. |
| Supports multiple AI models (OpenAI, Gemini, Claude, Mellum) for flexibility. | AI features depend on monthly credit quotas, which may feel restrictive. |
| Enterprise plan offers enhanced privacy, security, and compliance controls. | Still evolving compared to Copilot’s broader community and ecosystem. |
| In-IDE AI chat for contextual help without leaving the coding environment. | Requires annual subscriptions, which may be less flexible than monthly plans. |
What is GitHub Copilot?
GitHub Copilot is an AI-powered coding assistant developed by GitHub in partnership with OpenAI, designed to help developers write code faster and more efficiently.
Built on models like OpenAI’s Codex and GPT-4, it offers real-time code suggestions, inline completions, and natural language to code generation directly within popular editors such as Visual Studio Code, Neovim, and JetBrains IDEs.
Beyond autocomplete, Copilot also supports pull request reviews, code explanations, and chat-based assistance, making it one of the most widely adopted AI software development assistants for both individual developers and enterprises.
Key Features of GitHub Copilot
GitHub Copilot is built to accelerate software development by acting as an AI pair programmer. Its core strengths lie in real-time code generation, natural language understanding, and seamless integration into widely used coding environments.
| Feature | Overview |
|---|---|
| Inline Code Suggestions | Offers real-time completions, lines, blocks, or entire functions based on your code context. |
| Natural Language to Code | Converts plain-language prompts or comments into executable code snippets. |
| Copilot Chat (Inline Chat) | It lets developers chat with Copilot within the editor, ask questions, debug, or generate tests. |
| Copilot Spaces & Knowledge Bases | Context-aware task support. It consolidates project notes, with Spaces, enterprise users can define knowledge bases to enrich chat responses. |
| Pull Request Summaries & Assistance | Generates summaries, PR descriptions, and review suggestions to streamline collaboration. |
| Coding Agent (Asynchronous Task Execution) | It assigns issues to Copilot. It runs GitHub Actions, drafts pull requests in the cloud, and flags completion for review. |
| Agents Panel (“Mission Control”) | A unified UI on GitHub.com to assign and monitor Copilot tasks directly without leaving your workflow. |
| Model Flexibility (Smart Mode & Multi-Model Support) | Latest releases offer GPT-5, Gemini 2.5 Pro, and other models, with automatic routing for optimal results based on task type. |
GitHub Copilot Pricing Overview
GitHub Copilot offers simple subscription tiers for individuals, businesses, and enterprises, making it accessible to solo developers, startups, and large organisations.
Pricing includes access to core features such as inline code suggestions, Copilot Chat, and pull request assistance, with enterprise plans adding advanced compliance and policy controls
| Plan | Price |
|---|---|
| Free | $0 |
| Team | $4 per month |
| Enterprise | $21 per month |
Pros and Cons of GitHub Copilot
GitHub Copilot is one of the most widely adopted AI software development assistants, but like JetBrains AI Assistant, it has both strengths and limitations developers should weigh before adoption.
| Pros | Cons |
|---|---|
| Works across multiple environments (VS Code, Neovim, JetBrains via plugin). | Less project-aware than JetBrains when handling large, complex codebases. |
| Strong real-time code generation and autocomplete for rapid development. | Concerns about intellectual property, since suggestions may reflect public code. |
| Tight integration with GitHub for pull requests, reviews, and collaboration. | Heavily reliant on cloud processing through OpenAI models. |
| Simple, predictable monthly pricing for individuals and teams. | Limited offline functionality compared to JetBrains’ multi-model flexibility. |
| Large global user base and community support with frequent updates. | Enterprise-grade compliance and privacy options are less extensive than JetBrains. |
5 Key Differences Between JetBrains AI Assistant vs Copilot
When it comes to choosing the right AI coding assistant for developers, the debate of JetBrains AI Assistant vs Copilot often comes up.
Both tools enhance productivity with features like code generation, explanations, and AI chat, but they diverge in crucial ways, ranging from features and functionality to pricing models, IDE integration, and enterprise readiness.
Understanding these differences helps developers and businesses decide which tool better aligns with their workflows and long-term goals.
Difference 1 – Integration and Ecosystem
One of the biggest distinctions in the JetBrains AI Assistant vs Copilot discussion lies in ecosystem integration. JetBrains AI Assistant is built directly into JetBrains IDEs such as IntelliJ IDEA, PyCharm, WebStorm, and others, offering deep, context-aware assistance tied to the project structure.
In contrast, GitHub Copilot integrates across a wider ecosystem, including Visual Studio Code, Neovim, and JetBrains via plugin, making it accessible to developers regardless of their preferred coding environment.
This means JetBrains users benefit from seamless, highly specialised support, while Copilot appeals to those seeking flexibility across multiple editors and platforms.
Difference 2 – Features and Functionality
When comparing JetBrains AI Assistant vs Copilot, their biggest divergence comes from what they prioritise.
JetBrains AI Assistant features focus on deep project understanding and developer productivity inside JetBrains IDEs, while Copilot features emphasise real-time AI code generation tools and collaboration within GitHub and popular editors.
| Tool | Core Features |
|---|---|
| JetBrains AI Assistant | Code explanations, intelligent refactoring, test generation, in-IDE AI chat, and documentation support |
| GitHub Copilot | Inline code suggestions, natural language to code, Copilot Chat, pull request assistance, code explanation |
Difference 3 – AI Models and Technology
Another important difference between JetBrains AI Assistant and Copilot lies in the AI engines powering them.
JetBrains AI Assistant uses multiple large language models (LLMs), including OpenAI, Google Gemini, Anthropic Claude, and its own Mellum model, giving developers flexibility and resilience if one provider changes.
Copilot, on the other hand, primarily relies on OpenAI’s Codex and GPT-4, with newer support for GPT-5 and Gemini 2.5 in enterprise tiers. This means JetBrains offers a multi-model ecosystem that adapts to different tasks, while Copilot provides a streamlined but more centralised experience.
Difference 4 – Pricing and Licensing
Pricing reveals a practical difference between JetBrains AI Assistant and Copilot. While both tools aim to make AI accessible to developers, they structure their subscriptions differently.
JetBrains AI Assistant ties pricing to AI Credit quotas within JetBrains IDE subscriptions, offering multiple tiers from free access to enterprise-grade plans.
GitHub Copilot, on the other hand, follows a simpler flat monthly subscription model, with plans tailored for individuals, teams, and large organisations.
| Plan or Tier | JetBrains AI Assistant | GitHub Copilot |
|---|---|---|
| Free | $0 – 3 AI Credits per month | $0 |
| Pro or Team | $100 per year – 10 AI Credits per month | $4 per month (Team plan) |
| Ultimate | $300 per year – 35 AI Credits per month | N/A |
| Enterprise | $720 per year – max credits, enterprise security, and custom AI integrations | $21 per month (Enterprise plan) |
In essence, Copilot pricing is more predictable and flexible for diverse teams, while JetBrains pricing aligns with developers already embedded in the JetBrains ecosystem who want scalable AI usage linked to their IDE subscriptions.
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Difference 5 – Privacy, Security, and Data Handling
The final major difference between JetBrains AI Assistant and Copilot lies in how each handles privacy and enterprise security.
JetBrains AI Assistant emphasises compliance and data control by limiting what information is sent to the cloud and giving enterprises options for tighter security and integrations. In contrast, GitHub Copilot relies heavily on cloud processing via OpenAI models, meaning snippets of code are transmitted externally, raising potential concerns for organisations with strict IP protection or compliance requirements.
For global enterprises, this makes JetBrains more appealing where security is a top priority, while Copilot suits teams prioritising speed and collaboration within GitHub’s ecosystem.
Which AI Coding Assistant is Right for You?
Choosing between JetBrains AI Assistant vs Copilot depends largely on your workflow, preferred development environment, and organisational needs.
JetBrains appeals to developers already invested in JetBrains IDEs who want deep project awareness, structured pricing, and stronger enterprise controls.
Copilot, on the other hand, is ideal for developers who value real-time code generation, seamless GitHub integration, and predictable team pricing.
| User Type | Best Choice | Why |
|---|---|---|
| Individual JetBrains Users | JetBrains AI Assistant | Tight IDE integration, project-aware refactoring, and AI Credits for control. |
| Freelancers or General Developers | GitHub Copilot | Works across VS Code, JetBrains (via plugin), and Neovim with simple pricing |
| Startups and Small Teams | GitHub Copilot | Affordable team plan ($4/month), quick setup, strong GitHub workflow fit |
| Enterprises with Compliance Needs | JetBrains AI Assistant (Enterprise) | Maximum credits, enterprise-grade security, and private integrations |
| Collaborative GitHub-First Teams | GitHub Copilot | Pull request reviews, AI chat, and coding agents optimised for GitHub use |
The Future of AI in Software Development
AI tools like JetBrains AI Assistant and GitHub Copilot are just the beginning of a larger transformation in software engineering.
From automating repetitive tasks to reshaping collaboration, AI software development assistants will play a defining role in how individuals, startups, and enterprises build technology.
Looking ahead, developers can expect deeper integrations, smarter automation, and new challenges around ethics and compliance.
| Trend | What It Means for Developers |
|---|---|
| Deeper IDE Integration | AI will become a native layer inside coding environments, offering project-wide context and insights. |
| Autonomous Coding Agents | Future assistants will not just suggest code but also run tasks, file issues, and create pull requests autonomously. |
| Enterprise-Grade Compliance | Demand for privacy-first AI with strict data controls will grow, especially for regulated industries. |
| Multi-Model Flexibility | Developers will increasingly choose from multiple LLMs (e.g., OpenAI, Gemini, Claude) depending on project needs. |
| Ethical & IP Considerations | AI-generated code will raise questions about copyright, ownership, and responsible usage. |
| Skill Shift in Development | Developers will focus more on problem-solving and design while AI handles boilerplate coding. |
Conclusion
Both JetBrains AI Assistant and GitHub Copilot showcase how far AI coding tools have come in reshaping software development. JetBrains is the go-to for developers seeking structured, IDE-focused intelligence, while Copilot shines for those who want fast, flexible code generation across platforms.
The future belongs to teams and individuals who learn to harness these assistants wisely to code smarter, faster, and more securely.
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Frequently Asked Questions (FAQs)
What is the main difference between JetBrains AI Assistant and Copilot?
JetBrains AI Assistant is tightly integrated into JetBrains IDEs with context-aware refactoring and explanations, while Copilot focuses on real-time code generation across multiple editors.
Is JetBrains AI Assistant free to use?
Yes, there is a free tier with 3 AI Credits per month, but advanced plans (Pro, Ultimate, Enterprise) require a paid annual subscription.
Which is better for enterprises: JetBrains AI Assistant or Copilot?
JetBrains AI Assistant is better suited for enterprises needing compliance, privacy, and on-premise flexibility, while Copilot is ideal for teams working heavily within GitHub’s ecosystem.
Can I use both JetBrains AI Assistant and Copilot together?
Yes, many developers use both. Copilot for fast inline code suggestions and JetBrains AI Assistant for project-specific refactoring, explanations, and test generation.
Does JetBrains AI Assistant work outside JetBrains IDEs?
No, JetBrains AI Assistant is exclusive to JetBrains IDEs, making it best suited for developers already working in that ecosystem.
Can GitHub Copilot be used in JetBrains IDEs?
Yes, GitHub Copilot offers a plugin for JetBrains IDEs, though it is not as deeply integrated as JetBrains’ own AI Assistant.
Which tool is better for collaborative GitHub workflows?
GitHub Copilot is the stronger choice for teams that rely on GitHub, as it integrates with pull requests, reviews, and shared repositories.
Do both tools support AI chat?
Yes, both offer AI chat, but JetBrains’ chat is IDE-focused for project context, while Copilot’s chat extends into pull requests and GitHub workflows.
