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JetBrains AI Assistant is the most direct starting point for IntelliJ IDEA in 2026 because it combines inline completion, next-edit suggestions, project-aware chat, coding agents, local models and provider/API-key options inside the JetBrains workflow. GitHub Copilot is the strongest alternative when your team already uses GitHub’s models and agent features. There is no published independent benchmark proving one assistant writes better code, so the right choice depends on the work you do, your IntelliJ edition, expected agent volume, model control and privacy requirements.
This guide compares the documented capabilities, eligibility rules, quotas and prices, then gives installation steps and a practical way to test both assistants on your own repository.
The short answer: which IntelliJ assistant should you choose?
Choose JetBrains AI Assistant when you want the most native IntelliJ experience, access to JetBrains’ completion and next-edit models, local-model support, multiple coding agents or the ability to bring your own provider credentials. Choose GitHub Copilot when your code, pull requests and team workflow already revolve around GitHub and you want Copilot’s supported agent mode in a JetBrains IDE.
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Those are conditional recommendations, not a quality ranking. The available official material documents integrations and plan terms, but does not establish a controlled head-to-head test, defect rate or productivity gain. Run the same representative task in each assistant before committing to a long-term plan.
#1 Best Overall
| Best fit | Starting choice | Why |
|---|---|---|
| Native IntelliJ completion and navigation | JetBrains AI Assistant | Integrated with JetBrains IDE features, project context and next-edit suggestions. |
| GitHub-centered development and reviews | GitHub Copilot | Copilot is available in JetBrains IDEs and supports agent mode, but requires its own subscription. |
| Local models or provider flexibility | JetBrains AI Assistant | JetBrains documents local models, provider credentials, API keys and ACP-compatible external agents. |
| Trying AI without paying | Depends on eligibility | Copilot Free lists 2,000 completions monthly; JetBrains AI Free has IntelliJ IDEA edition restrictions. |
What IntelliJ supports in 2026
JetBrains describes AI Assistant as a plugin compatible with IntelliJ IDEA and almost all other JetBrains IDEs. Its feature set includes single-line and block autocomplete, next-edit suggestions, context-aware chat using project files, folders, symbols and commits, multi-step coding agents and MCP tools. The documented agent choices include Junie, Claude Agent, Codex and GitHub Copilot, while ACP-compatible external agents can also be connected. These are documented capabilities, not evidence that every agent performs equally well on your codebase. JetBrains AI Assistant documentation
IntelliJ IDEA 2026.1 release notes specifically call out next-edit suggestions for Java, Kotlin and Scala. If your project uses another language, verify the current language coverage in the IDE and assistant documentation rather than assuming that the same feature scope applies. IntelliJ IDEA 2026.1 release notes
JetBrains AI Assistant: capabilities, plans and limitations
What it does inside the IDE
- Inline completion: suggestions for a line or a larger code block while you type.
- Next-edit suggestions: predicts the next location and change after an edit, reducing repetitive navigation.
- Project-aware chat: can use selected files, folders, symbols and commits as context.
- Coding agents: agents can plan multi-step changes; the documented list includes JetBrains’ own agents and connected third-party options.
- Model choice: JetBrains documents provider credentials, API-key use and local models, which can matter when policy or latency rules prevent sending code to a hosted service.
- Extensibility: MCP tools and ACP-compatible external agents can add tools or agents beyond the default set.
JetBrains plan structure
The JetBrains FAQ lists AI Free, AI Pro, AI Ultimate and AI Enterprise. The exact regional price for every tier is not established in the accessible FAQ, so check the live plan page before purchase. The concrete individual example in the FAQ is AI Ultimate at USD 30 per month with USD 35 in AI Credits. That figure is an example of the stated plan terms, not a universal regional quote; taxes, currency and eligibility may change. JetBrains AI FAQ
AI Free includes unlimited completion using JetBrains’ Mellum model, unlimited use of connected local models and a limited cloud quota. However, JetBrains states that AI Free is not available in IntelliJ IDEA without an Ultimate IDE subscription. A user on IntelliJ IDEA Community should therefore not assume that the free AI tier will appear merely because it exists in the product lineup.
The FAQ describes a 30-day AI Pro trial for first activation. Included quota resets every 30 days from the date of first activation; unused included quota does not roll over. Purchased top-up credits remain valid for 12 months. Completion and next-edit suggestions use JetBrains-trained models and do not consume AI quota, while cloud chat and agent workloads draw from the applicable quota.
Some license holders, including All Products Pack and dotUltimate users, may receive AI Pro at no additional cost, subject to JetBrains’ listed exceptions. Verify the entitlement in your account because a qualifying bundle, IDE edition and organization policy all affect what you see.
When JetBrains AI is the better fit
- You want completion and chat controlled from JetBrains settings rather than a separate extension workflow.
- You need to combine hosted models with a local model or your own provider credentials.
- You expect to switch among several agents instead of committing to one vendor’s agent.
- Your main work is Java, Kotlin or Scala and next-edit assistance is a priority.
- Your organization wants centralized controls over data sharing and allowed providers.
GitHub Copilot in IntelliJ: what is included
GitHub Copilot is supported in JetBrains IDEs and can appear as an integrated agent in JetBrains AI Chat. Authentication uses GitHub OAuth. An active GitHub Copilot subscription is required; a JetBrains AI subscription does not include Copilot access. JetBrains announcement about the integrated Copilot agent
GitHub’s individual plan page lists four tiers. Copilot Free costs USD 0 and lists 2,000 completions per month. Pro costs USD 10 per user per month, Pro+ costs USD 39, and Max costs USD 100. The same page lists monthly total AI-credit values of USD 15, USD 70 and USD 200 for Pro, Pro+ and Max respectively. GitHub Copilot plans and pricing
GitHub’s documentation expresses those paid allowances as 1,500, 7,000 and 20,000 credits, with one credit equal to USD 0.01. Chat and agent interactions consume credits; completions and next-edit suggestions do not. Model selection and task complexity affect consumption, so a subscription price is not a guarantee of unlimited agent work. GitHub documentation on Copilot plans
Copilot Free has additional eligibility conditions for individuals without organizational access. A company-managed account may expose different policies, limits or model availability. Confirm the account type and current terms before treating the free plan as a production option.
When Copilot is the better fit
- Your repositories, issues and pull requests are already managed in GitHub.
- Your team has standardized on Copilot policies, billing and model access.
- You prefer one paid account that follows you across supported environments, including JetBrains IDEs.
- You can estimate agent usage in credits and want the Pro, Pro+ or Max allowance to match that workload.
2026 pricing and quota comparison
| Option | Published price evidence | Published usage allowance | Important qualification |
|---|---|---|---|
| JetBrains AI Free | USD price not stated in the accessible FAQ | Unlimited Mellum completion, unlimited connected local-model use and limited cloud quota | Not available in IntelliJ IDEA without an Ultimate IDE subscription. |
| JetBrains AI Pro | Full numeric price not stated in the accessible FAQ | Quota depends on the current plan | A 30-day first-activation trial is described; check current regional terms. |
| JetBrains AI Ultimate | USD 30/month example | USD 35 in AI Credits in that example | Included quota resets every 30 days from activation; unused quota does not roll over. |
| JetBrains top-up credits | Purchase price varies | Purchased credits remain valid for 12 months | Confirm current price and regional availability before relying on top-ups. |
| GitHub Copilot Free | USD 0 | 2,000 completions per month | Free eligibility and chat/agent limits apply. |
| GitHub Copilot Pro | USD 10/user/month | USD 15 monthly total credits, documented separately as 1,500 credits | Agent and chat interactions consume credits; completions and next edits do not. |
| GitHub Copilot Pro+ | USD 39/user/month | USD 70 monthly total credits, or 7,000 credits in GitHub documentation | Compare model access and expected agent volume, not price alone. |
| GitHub Copilot Max | USD 100/user/month | USD 200 monthly total credits, or 20,000 credits in GitHub documentation | Intended for higher-volume use; verify current limits and terms. |
Prices and quotas are volatile. The figures above are the published values identified for 2026 and can change by region, tax treatment, renewal date or product revision. A complete numeric comparison for every IntelliJ-compatible competitor and API-key provider is not established here; do not infer missing prices from this table.
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Inline completion versus multi-file agents
If most of your time is spent accepting short suggestions, class scaffolds or repetitive tests, completion quality and latency matter more than agent credits. JetBrains says completion and next-edit suggestions do not consume AI quota, and GitHub says completions and next edits do not consume Copilot credits. For a completion-heavy workflow, compare how often each suggestion is accepted on your own files rather than comparing monthly prices.
If you ask the assistant to inspect a repository, edit several files, run tests and revise failures, model context and credit consumption become central. Count those tasks separately from completion volume. A plan that looks inexpensive for autocomplete can become expensive when used as a continuous agent.
Model and provider control
JetBrains documents local models, provider credentials, API keys, MCP tools and ACP-compatible agents. This is useful when you need to keep some work on-premises, use an existing provider contract or select a model for a particular language. It also means you must understand which context each configuration sends outside the IDE.
Copilot offers a more opinionated account and model experience. That can simplify administration for a GitHub-standardized team, but it gives you less reason to mix unrelated providers inside one IntelliJ configuration. Check the current model catalog and organization policy before promising a specific model to developers.
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For Java, Kotlin and Scala, IntelliJ IDEA 2026.1 explicitly documents next-edit suggestions. For large monorepos, generated code, unusual build systems or less common languages, test the assistant against real modules, compiler settings and repository conventions. Feature lists establish that a function exists; they do not establish that generated code compiles or follows your architecture.
Install and configure JetBrains AI Assistant
- Open IntelliJ IDEA and select Settings on Windows/Linux or Preferences on macOS.
- Open Plugins, search for AI Assistant, install the JetBrains plugin and restart the IDE if prompted.
- Sign in with the JetBrains Account that owns your IDE entitlement. If the AI panel reports that AI Free is unavailable, check whether the IDE is IntelliJ IDEA without an Ultimate subscription.
- Open the AI Assistant tool window and review the active plan, remaining cloud quota and available agents.
- In AI settings, choose the provider or model allowed by your organization. If you use a local model or API key, verify the endpoint, authentication and data-routing policy before opening proprietary files in chat.
- Enable inline completion and next-edit suggestions only after checking their language scope and keyboard shortcuts. Keep ordinary IDE completion available so you can compare suggestions.
- For a repository task, select the smallest useful context: a file, folder, symbol or commit. Deliberately adding the entire repository can increase exposure and make answers less precise.
- Run a harmless task first, such as explaining a test or proposing a narrowly scoped refactor. Review the diff manually and confirm that no unrequested files changed.
Connect GitHub Copilot in IntelliJ
- Install or enable the GitHub Copilot integration available for your JetBrains IDE version.
- Start the sign-in flow and complete GitHub OAuth in the browser.
- Confirm that the GitHub account has an active Copilot plan or an eligible organizational seat. A JetBrains AI plan alone does not authorize Copilot.
- Open JetBrains AI Chat and select the Copilot agent where it is offered. Review the agent’s requested tools, files and commands before approving them.
- Check the Copilot usage view in GitHub so you can distinguish completion activity, chat requests and agent-credit consumption.
- Ask the agent to make a small, reversible change, run the project’s normal tests yourself and inspect the resulting diff.
A fair 30-minute comparison you can run on your repository
Because no independent benchmark establishes a universal winner, use a repeatable task rather than impressions from a demo. Do not paste secrets, credentials or regulated data into either service.
- Choose one representative issue that has a clear acceptance test, such as adding validation, fixing a failing test or introducing a small endpoint.
- Create a fresh branch and record the baseline test command, runtime and failing assertions.
- Give each assistant the same issue description and the same selected files. Do not let one assistant see hidden context that the other lacks.
- Measure whether the first proposal compiles, how many files it changes, how many manual corrections are needed and whether tests pass.
- Repeat with a completion task, a code-explanation task and a multi-file agent task. Keep completion acceptance separate from agent-credit usage.
- Review security and maintainability: dependency changes, logging of sensitive values, authorization checks, error handling and adherence to your project’s conventions.
- Record the model, plan, date and settings. A later model update or quota change can invalidate an old conclusion.
This approach gives you a local decision based on your language mix, build tools and review standards without claiming that a small sample proves general superiority.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Privacy, data sharing and administration
JetBrains says data sharing is opt-in for paid licenses, including individual and company licenses and trials. For non-commercial licenses, data sharing is enabled by default but can be disabled in settings. Company policies can be centrally maintained by administrators. Confirm the current policy and your organization’s configuration before using proprietary code. JetBrains AI privacy and plan FAQ
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Best Value
- Use separate settings profiles for personal and employer repositories.
- Exclude secret files, generated credentials and production configuration from assistant context.
- Require human review for authentication, authorization, cryptography, database migrations and infrastructure changes.
- Log which assistant and model produced a change when your compliance process requires traceability.
- Disable automatic command execution unless the agent can run in a sandbox with least-privilege credentials.
Common pitfalls and fixes
“The free JetBrains tier is missing”
Check the IntelliJ IDEA edition and the signed-in JetBrains Account. JetBrains AI Free is not available in IntelliJ IDEA without an Ultimate subscription, so the absence may be an eligibility rule rather than a plugin failure.
“Copilot appears, but chat or agent actions stop”
Verify that the GitHub account has an active Copilot subscription or organizational seat. Then inspect credit usage: chat and agent interactions consume credits even when completions continue to work.
“The assistant changed too much code”
Reduce the selected context, ask for a plan before edits, approve one file at a time and review the diff after every agent step. Revert the branch and restate the acceptance test if the agent broadens scope.
“Suggestions are inaccurate for this project”
Provide the relevant symbol, interface, test and build constraint instead of the whole repository. Check indexing, language support and generated-source configuration in IntelliJ, then repeat the same task with a smaller context window.
“Quota ran out unexpectedly”
Separate non-metered completion from metered chat and agent activity. For JetBrains, check the 30-day reset date and whether unused quota expired rather than rolled over. For Copilot, inspect the credit units and model/task mix; a complex agent request can consume more than a short chat.
Bottom-line decision
Start with JetBrains AI Assistant if IntelliJ integration, local or bring-your-own models and multiple agents are your priorities. Start with GitHub Copilot if your team already pays for and governs GitHub’s coding workflow. Confirm your IntelliJ edition, calculate likely chat and agent volume, and run the same controlled task on your own code before choosing a paid tier. Neither product’s published feature list is a substitute for that repository-specific test.
Quick Recap
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