JetBrains AI vs Copilot: Features and Pricing Compared

The short answer is that JetBrains AI Assistant is the natural fit for a JetBrains-centered workflow, while GitHub Copilot is the more flexible pick when you move between editors. Your development work may happen mostly in one familiar IDE, or across several tools. That difference can shape your experience, the time you spend switching contexts, and the choice that feels practical.

An AI credit equals $1.00 of AI use at public API rates within JetBrains AI in 2026. The comparison ahead looks at features, models, setup, and price, so you can weigh each tool against your daily work. The best choice is the one that helps you make and review changes without disrupting the way you already work.

Key Takeaways

• JetBrains AI Assistant keeps AI help within JetBrains IDEs.
• GitHub Copilot supports work across different editors.
• The Copilot plugin and its AI Assistant integration are separate access paths.
• Plan allowances and credit rules differ between the products.
• Test both tools on the same real project task.

What Are JetBrains AI Assistant and GitHub Copilot?

GitHub Copilot is a separate product from JetBrains AI Assistant, even though you can now access its agent from JetBrains AI chat. GitHub is the company and platform; GitHub Copilot is its coding assistant. The distinction matters because Copilot can appear through a JetBrains plugin or inside JetBrains AI Assistant.

Those options use different access paths and sign-ins. The standalone plugin runs in a JetBrains IDE through your GitHub account. The agent integration appears in JetBrains AI Assistant and needs GitHub OAuth plus an active Copilot subscription.

GitHub Copilot became a first-class option in the JetBrains AI Assistant agent picker on June 30, 2026. The integration needs an updated IDE. To start installing JetBrains AI Assistant, open the IDE widget and select “Let’s Go.”

GitHub is not a third coding assistant in this comparison; it is the company and platform behind GitHub Copilot.

The standalone plugin also offers Copilot CLI commands, including /remote and /chronicle, in JetBrains AI chat. So “JetBrains AI vs Copilot vs GitHub” compares two assistants, not three.

Check which product and sign-in flow you are using before comparing what each subscription includes.

What Can Each Assistant Do in a Coding Workflow?

Inline suggestions fit small, immediate edits, while an agent is useful when a request needs several coordinated steps. Small edits can mean finishing a line, changing a method, or asking a chat window to explain an unfamiliar block. In either case, you guide the work and decide what code to keep.

Suggestions are drafts, not automatic approval. JetBrains AI Assistant and GitHub Copilot can help with code generation, questions, and requested changes. You still choose which edits enter your project.

Inline completions, chat, and guided tasks

Inline completions appear near the code you are writing, letting you accept or ignore a suggestion. In-IDE chat supports questions about code and requests for changes. Ask mode in the GitHub Copilot JetBrains plugin offers another way to discuss a task before editing.

The plugin supports completions, Ask mode, Agent Mode, planning, and Model Context Protocol connections. Its JetBrains plugin feature list describes those tools and their role in the IDE. Use chat for a narrow question, such as asking why a test fails, then judge the answer against your code.

Agent Mode and multistep project changes

An agent can take several steps toward a larger request. For example, you might ask it to fix a reported error. Copilot Agent Mode in a JetBrains IDE can suggest and run commands, address errors, and revise work after your feedback.

The Copilot agent reached through JetBrains AI Assistant is a separate route from Agent Mode in the standalone Copilot plugin. The AI Assistant agent can handle multistep coding tasks, propose project changes, run commands, and iterate with you. The plugin’s Agent Mode can also plan work and respond to feedback.

These features can touch several files, so inspect the proposed changes and command effects. For broader comparisons of assistants and agents, see AI tools for coding workflows. Review each proposed file change and command before allowing an agent-driven task to become part of your project.

JetBrains AI vs Copilot: Which Fits Your IDE and Project Context?

If your work stays inside JetBrains IDEs, JetBrains AI Assistant is the closer workflow fit; if you switch editors, GitHub Copilot is the more flexible option. Your IDE habits are a useful first test. A developer who opens IntelliJ IDEA, WebStorm, or PyCharm all day may prefer one AI interface there.

IDE fit does not prove that an assistant understands your codebase better. Project context depends on the task and the code around it. Test suggestions against a real project pattern instead of assuming either tool understands every repository.

GitHub Copilot’s JetBrains plugin supports Java, PHP, Python, JavaScript, Ruby, Go, C#, and C++ in 2026. That list gives you concrete languages to try, but language support alone cannot ensure accurate project-specific code.

For example, a completion may use valid Python yet miss a local naming rule or an existing service pattern. The same risk applies when an assistant proposes refactoring across a codebase. Look at the surrounding files and the way your project handles similar work.

GitHub Copilot can suit developers who move between JetBrains IDEs and other editors, including Visual Studio Code. JetBrains AI Assistant can suit developers who want AI interaction centered in JetBrains. If you compare editors as well as assistants, this guide to code editors and IDEs outlines how editor fit can shape a workflow.

For a JetBrains AI comparison, focus on IDE fit, project context, and whether the code matches patterns already in your repository. Try each tool on a familiar task that touches an existing project pattern before judging the quality of its context.

Which Models and External Agents Can You Use?

JetBrains AI gives you more than one way to connect an AI provider, but the available choices depend on the connection method. The connection path decides whether you use an existing provider account, your own API key, or JetBrains AI credits.

Provider access and JetBrains AI credits are separate ways to pay for use. Connecting an existing account does not mean that every model or agent appears in every IDE. Check the specific choices available in your setup.

Models and provider accounts in JetBrains AI

JetBrains AI users can select supported GitHub Copilot models in AI chat and adjust reasoning depth. That gives you some control over how the assistant handles a request. Model options depend on the supported connection and the IDE.

Using an existing provider account differs from spending JetBrains AI credits. The account path connects the provider you already use. JetBrains AI credits track AI use within JetBrains AI, so do not treat the two paths as one balance.

ACP agents and bring-your-own API keys

Agent Client Protocol (ACP) is a way to connect supported agents to JetBrains AI. JetBrains AI supports more than 25 agents through ACP using existing provider accounts. Supported connections include Cursor, Codex, and GitHub Copilot.

API keys offer another route. JetBrains AI supports users’ own API keys for Anthropic, OpenAI, and Google. An API key connects to a service, while ACP connects a supported agent through a provider account.

These options give you choices, but they do not guarantee that every model or agent works in every IDE. If you are comparing coding tools beyond these providers, this AI app overview includes options such as Cursor and Google AI Studio.

Before settling on a setup, check whether you want to use a provider account, an API key, or JetBrains AI credits.

How Much Do JetBrains AI and Copilot Cost in 2026?

JetBrains AI Free costs nothing, JetBrains AI Pro and Ultimate cost $100 and $300 per user per year, and GitHub Copilot individual plans range from $10 to $100 per month. The headline prices use different billing periods, so compare the included use as well as the fee.

JetBrains AI Pro includes 10 monthly AI credits, while Copilot Pro includes 1,500 monthly AI credits. Those credit systems have different rules, so their numbers are not directly interchangeable.

JetBrains AI Free, Pro, and Ultimate

JetBrains AI Assistant pricing includes a free plan and two paid yearly plans. All three include unlimited AI completion, while their AI credit amounts differ.

JetBrains AI Free has exceptions: it is unavailable in Android Studio, IntelliJ IDEA without an Ultimate subscription, and PyCharm without a Pro subscription. Check that rule against the IDE you use before counting on free access.

GitHub Copilot individual plans

GitHub Copilot pricing includes three paid individual plans. Copilot Free is also available, with a monthly completion limit instead of a stated AI credit allowance.

Copilot Free allows 2,000 inline code completions per month. Those completions are not AI credits. The paid plan amounts and prices are listed in GitHub Copilot plan allowances.

Credits, renewals, and top-ups

A JetBrains AI credit equals $1.00 of AI use at public API rates within JetBrains AI in 2026. Monthly credits renew every 30 days, and unused credits do not roll over. Pro and Ultimate users can buy top-up credits that remain valid for 12 months after purchase.

Those rules make the timing of your use matter. A credit that remains unused at renewal does not carry forward, while a top-up has a longer validity period.

Compare the included AI allowance you will actually use, not just the subscription’s headline price.

Which Assistant Fits Your Everyday Development Workflow?

For most developers who already work mainly in JetBrains IDEs, JetBrains AI Assistant is the easiest workflow fit; Copilot wins when editor flexibility matters more. Your daily routine is a better guide than a long feature list. IntelliJ IDEA, WebStorm, and PyCharm all keep you within JetBrains tools.

GitHub Copilot is the more direct fit for GitHub-centered work, while JetBrains AI Assistant keeps AI interaction inside a JetBrains IDE. Developers who also use Visual Studio Code may value a tool that moves with them between editors.

Use these common situations to make the choice concrete:

• JetBrains-only workflow: Start with JetBrains AI Assistant.
• Frequent editor switching: Try GitHub Copilot.
• GitHub-centered development: Start with GitHub Copilot.
• Control over model or provider access: Compare JetBrains AI connection options.

The last situation calls for a closer look at the model and provider choices you can connect. A developer who values control may prefer the setup that fits existing provider access, while another may want one IDE-based interface.

Your project matters, too. A familiar framework or a local code pattern can expose gaps that a small sample file hides. Give both assistants a similar task in a project you know, then judge how much guidance and correction each needs.

If your workflow crosses editors, a developer coding assistant comparison can help you weigh editor fit against repository tasks. Choose the tool that reduces friction in your normal work rather than adding another place to manage code.

How Should Developers Keep Control of AI-Generated Code?

Treat an AI suggestion as a draft to verify, not as evidence that a change compiles, behaves correctly, or is secure. Generated code can contain syntax errors or logical errors, even when it looks neat. You remain responsible for whether the implementation fits your project.

Tests can repeat a mistake when they are written to match faulty code. A generated test may confirm the same mistaken logic as an incorrect implementation. Passing those tests does not prove that the change meets the real requirement.

This risk can be harder to spot when the code uses patterns you do not know well. Ask the assistant to explain a change or simplify a complex block, then use that explanation to reason through the behavior yourself.

Test-driven development and behavior-driven development set tests before implementation. That order gives you a separate check against the intended behavior. It can help reveal when generated tests merely echo the code they are meant to test.

Security needs the same care as function and style. The NIST Secure Software Development Framework recommends security practices throughout the software life cycle. It does not certify AI-generated code, so your own checks still matter.

For broader advice on reviewing generated changes, see ways to assess coding assistants. Run the project’s own checks and read every changed line before accepting an AI-generated implementation.

How Do You Install Copilot in WebStorm and Other JetBrains IDEs?

You can install GitHub Copilot in WebStorm and the other listed JetBrains IDEs through the IDE’s Plugins Marketplace. WebStorm is compatible, along with IntelliJ IDEA, CLion, DataGrip, GoLand, PhpStorm, PyCharm, Rider, RubyMine, and RustRover.

The setup takes three steps: install the plugin, restart the IDE, and sign in to GitHub. The plugin provides code completions and in-IDE chat after setup.

Check plugin compatibility

GitHub Copilot supports the JetBrains IDEs listed above in 2026. If you use WebStorm for JavaScript work, you can install the plugin there. The same compatibility list includes IDEs for other languages and project types.

In 2026, the GitHub Copilot plugin’s JetBrains Marketplace listing had a 2.1 rating from 1,441 ratings. That is a marketplace snapshot, not proof of the plugin’s quality or performance in your project.

Install the plugin and sign in

Open your JetBrains IDE and follow these steps:

1. Install GitHub Copilot from the IDE’s Plugins Marketplace.
2. Restart the IDE.
3. Sign in to GitHub when the plugin prompts you.

After signing in, try a small change in a familiar project and check that the suggestions fit your codebase.

What Should Teams Check Before Standardizing?

For teams, the key budgeting difference is that Business and Enterprise assign monthly credits per user into a shared pool. Seat costs matter, but team leads also need to plan how the pool will cover premium AI use.

Business costs $19 per granted seat monthly, while Enterprise costs $39 per granted seat monthly. Each plan’s monthly credits contribute to a shared team pool.

Business and Enterprise credits combine in a shared pool. Usage beyond that pool costs $0.01 per AI credit. GitHub Copilot inline suggestions, including next edit suggestions, remain unlimited and use no credits, even at an enforced spending limit.

Set a spending limit before rollout, and make clear which developers receive seats and how shared credits work.

Copilot Free is only for individual developers without organization or enterprise access. It also provides model access through automatic model selection only.

Before a team adopts a standard, use this checklist:

• Confirm which developers receive seats.
• Estimate premium AI use against the shared pool.
• Set an enforced spending limit.
• Check which Free users are ineligible.

Before rollout, make the seat and spending-limit rules clear to every developer who will use the tool.

Conclusion

Choose JetBrains AI Assistant for a JetBrains-centered workflow, or GitHub Copilot when moving between editors matters most. Your own project is the fairest place to test that choice, since it shows how each tool handles your real code and habits.

Give both assistants the same task, such as updating a familiar pattern or fixing a known issue. Then compare the changes you need to make and how easily you can check the result. Test both on the same representative task in your own project, then keep the one whose output you can review and use with confidence.