AI-powered plugin for JetBrains IDEs that enhances development workflow with intelligent code completion, next edit suggestions, AI chat with agent mode, and context management features.
JetBrains AI Assistant is a deeply integrated AI-powered plugin available across the entire JetBrains IDE family â including IntelliJ IDEA, PyCharm, WebStorm, GoLand, Rider, CLion, PhpStorm, RubyMine, DataGrip, and RustRover â that combines local and cloud-based AI models to deliver intelligent code completion, conversational AI chat, and autonomous agent capabilities directly within the developer's workflow.
At its core, JetBrains AI Assistant uses a hybrid model architecture. The proprietary Mellum model handles local code completion with a median latency under 200 milliseconds, processing over 90% of completion requests without transmitting code to external servers. For more complex tasks like multi-file code generation, architectural explanations, and agent-driven workflows, the plugin connects to cloud LLM providers including OpenAI (GPT-4o, GPT-4.1), Google (Gemini 2.5 Pro, Gemini 2.5 Flash), and Anthropic (Claude Sonnet 4), giving developers the flexibility to choose the model best suited to each task.
The standout feature in 2026 is Junie, JetBrains' autonomous agent mode. Junie can plan and execute multi-step development tasks â writing code, generating tests, running them through the IDE's built-in test runner, interpreting failures, and iterating until tests pass â all without manual intervention. In internal benchmarks, Junie reduced boilerplate test-writing time by approximately 60% for JUnit and pytest scaffolds. The agent operates within a sandboxed environment scoped to the local project, ensuring it cannot make unintended changes to external systems.
JetBrains AI Assistant supports over 10 JetBrains IDEs with a single plugin installation, covering more than 20 programming languages including Java, Kotlin, Python, JavaScript, TypeScript, Go, Rust, C++, PHP, and Ruby. The plugin processes an estimated 15 million code completions daily across its user base, with acceptance rates averaging 30% for single-line suggestions and 22% for multi-line completions.
Context management is another differentiator: developers can attach specific files, folders, symbols, commits, images, and other project artifacts to AI chat conversations, giving precise control over the information the model receives. This targeted context approach reduces hallucination rates compared to tools that rely solely on automatic retrieval, with JetBrains reporting a 25% improvement in response relevance when explicit context is provided versus automatic-only context.
The free tier provides limited daily AI code completions and chat messages, suitable for evaluation but not sustained professional use. The AI Pro tier at $8.33 per month (billed annually at $100/year) unlocks full access to all cloud models, Junie agent mode, increased usage limits, MCP server support, and local model configuration. For organizations already subscribed to the All Products Pack at $28.90/month per user billed annually, AI Pro features are included at no additional cost â making it one of the most cost-effective AI coding assistants for teams standardized on JetBrains tooling.
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JetBrains' proprietary Mellum model runs entirely on your local machine, providing single-line and multi-line code completions with a median latency under 200 milliseconds. It adapts to your coding style by analyzing project context locally, and processes over 90% of completion requests without sending any code to external servers â making it suitable for environments with strict data residency requirements.
Junie is an autonomous AI agent that can plan and execute multi-step coding tasks within the IDE. It writes code, generates tests, runs them via the IDE's built-in test runner, interprets results, and iterates on failures until tests pass. Junie operates in a sandboxed environment scoped to the local project and supports task decomposition for complex workflows like scaffolding new modules, migrating API versions, or generating comprehensive test suites.
The AI predicts the next location in your file that likely needs editing and pre-populates suggested changes. You can quickly accept a suggestion and jump to the next predicted edit point, streamlining workflows like renaming variables across a function, updating method signatures, or applying repetitive patterns â reducing the number of manual cursor movements and keystrokes needed for common editing sequences.
Developers can explicitly attach files, folders, images, symbols, commits, and other project artifacts to AI chat conversations. This gives fine-grained control over exactly what context the AI receives, reducing hallucination rates and improving response relevance by an estimated 25% compared to automatic-only context retrieval approaches used by other tools.
AI Chat and generation features support selecting from multiple cloud LLM providers, including OpenAI (GPT-4o, GPT-4.1), Google (Gemini 2.5 Pro, Gemini 2.5 Flash), and Anthropic (Claude Sonnet 4). Users can switch models per conversation based on the task at hand, and configure local third-party models for organizations that require on-premises inference without external API calls.
$0/month
$8.33/month (billed annually at $100/year)
$28.90/month per user for organizations (billed annually)
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In 2026, JetBrains significantly expanded Junie agent mode capabilities, adding more autonomous task execution and improved test iteration. The 2026.1 release introduced MCP (Model Context Protocol) server support, enabling developers to connect external tools and data sources to AI conversations. Local model configuration was enhanced to support a broader range of third-party models for both completion and generation. Next edit suggestions were refined with better cross-file prediction accuracy, and context management gained support for attaching images and commit diffs to chat conversations.
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