JetBrains AI Assistant vs Sourcegraph Cody

Detailed side-by-side comparison to help you choose the right tool

JetBrains AI Assistant

AI Coding Tools

AI-powered plugin for JetBrains IDEs that enhances development workflow with intelligent code completion, next edit suggestions, AI chat with project context, and coding assistance inside JetBrains IDEs.

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Starting Price

Custom

Sourcegraph Cody

🔴Developer

Developer Tools

Sourcegraph Cody is an enterprise AI coding assistant that uses Sourcegraph code context to help developers search, understand, write, and fix code.

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Starting Price

Custom

Feature Comparison

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FeatureJetBrains AI AssistantSourcegraph Cody
CategoryAI Coding ToolsDeveloper Tools
Pricing Plans4 tiers206 tiers
Starting Price
Key Features
  • Mellum Local Code Completion
  • Junie Agent Mode
  • Next Edit Suggestions
  • AI coding assistant for understanding, writing, and fixing code
  • Available in VS Code, JetBrains, Visual Studio, Sourcegraph web app, and CLI
  • Developer chat, code completions, code edits, and customizable prompts

💡 Our Take

Choose JetBrains AI Assistant when the main need is day-to-day AI coding help inside JetBrains IDEs, including completion, chat, next edit suggestions, and applying generated changes from the editor. Choose Sourcegraph Cody if your priority is codebase-wide search, repository-scale context retrieval, and understanding large codebases across tools.

JetBrains AI Assistant - Pros & Cons

Pros

  • Deep native integration with JetBrains IDEs lets developers use AI assistance inside IntelliJ IDEA, PyCharm, WebStorm, GoLand, Rider, CLion, PhpStorm, RubyMine, DataGrip, DataSpell, Aqua, and related products instead of switching to a separate AI editor.
  • The 2026.1 IntelliJ IDEA Help page lists concrete workflow features: code completion, next edit suggestions, AI Chat, agent mode, context management, response processing, cloud LLM support, and local model use.
  • AI Chat can use explicit project context such as files, folders, images, symbols, commits, and other items, which is useful for questions tied to a real codebase rather than isolated snippets.
  • Response processing is practical inside the IDE because developers can review AI output and then apply code snippets, modify single or multiple files, or run terminal commands directly from AI Chat.
  • Pricing includes a no-cost AI Free tier with 3 AI Credits per 30 days and paid individual tiers starting at $10 USD per 30 days, which makes evaluation easier for existing JetBrains users before an organization rollout.
  • Supports both cloud-based providers named in the documentation, including Google Gemini, OpenAI, and Anthropic, and custom local third-party models for supported features such as code completion, in-editor code generation, or commit message generation.

Cons

  • JetBrains AI Assistant is not bundled or enabled by default; users must install the plugin, have a JetBrains AI Service license, and explicitly accept JetBrains AI terms before it can access code.
  • It is limited to the JetBrains IDE ecosystem, so teams using VS Code, Neovim, Sublime Text, or browser-based development environments will not get the same native plugin experience.
  • Cloud usage is quota-based: AI Free includes 3 AI Credits per 30 days, AI Pro includes 10 individual or 20 organization credits, and AI Ultimate includes 35 individual or 70 organization credits, so heavy agent or chat usage may require top-ups or a higher tier.
  • Advanced workflows such as agent mode, multi-file edits, terminal command execution, and generated tests still require careful developer review before code is merged.
  • Local model support exists, but setup and capability coverage are narrower than cloud use; the supplied data notes that MCP tool invocation is not currently supported when using local models.

Sourcegraph Cody - Pros & Cons

Pros

  • Codebase-wide context is useful for large repositories, monorepos, and cross-service discovery
  • Supports multiple developer surfaces: VS Code, JetBrains, Visual Studio, web app, and CLI
  • Enterprise plan includes Sourcegraph platform capabilities such as Full MCP Server, API, CLI, security/admin controls, and 24x5 support
  • Strong fit for onboarding, code explanation, test generation, and finding existing implementation patterns

Cons

  • Enterprise starting price of $16K can be too high for solo developers and small teams
  • Final cost depends on seats, AI feature credits, deployment model, and support terms that must be confirmed with sales
  • Quality depends on Sourcegraph indexing, repository permissions, codebase hygiene, and human code review
  • Teams that only need lightweight autocomplete may find Cody more platform-heavy than necessary

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