Continue vs Cody by Sourcegraph

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

Continue

🔴Developer

Developer Tools

Open-source AI coding assistant for VS Code and JetBrains — bring any model, any MCP server, and share reusable rules and agents across your team via Continue Hub.

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Starting Price

Free

Cody by Sourcegraph

🔴Developer

AI Development Assistants

Cody is Sourcegraph's AI coding assistant that uses the Sourcegraph code graph for repo-wide context, ships across VS Code/JetBrains/CLI, and is priced from $0 Free to $16/user/month Pro and Enterprise custom.

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Starting Price

Free

Feature Comparison

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FeatureContinueCody by Sourcegraph
CategoryDeveloper ToolsAI Development Assistants
Pricing Plans4 listed plans4 listed plans
Starting PriceFreeFree
Key Features
  • • Multi-model AI support including OpenAI, Claude, Gemini, and local models
  • • Native IDE extensions for VS Code and JetBrains with smooth workflow integration
  • • MCP server connectivity for development toolchain integration
  • • AI-powered code completion with codebase context
  • • Natural language chat for code Q&A and generation
  • • Auto-edit suggestions based on cursor and editing patterns

Continue - Pros & Cons

Pros

  • ✓Open-source assistant for VS Code and JetBrains. This directly supports the primary workflow.
  • ✓Bring-your-own-model: Anthropic, OpenAI, Ollama, local, any provider.
  • ✓First-class MCP client — any MCP server becomes callable tools.
  • ✓Continue Hub for sharing assistants, rules, prompts across a team.

Cons

  • ✗At least one tier requires a sales quote, preventing a complete public budget calculation.
  • ✗Features and limits can change by plan, billing interval, region, and release; verify current documentation.
  • ✗MCP connectivity expands the permission surface and requires narrow scopes, approvals, logs, and credential rotation.
  • ✗A representative pilot is necessary because a feature list does not establish reliability or operational fit.

Cody by Sourcegraph - Pros & Cons

Pros

  • ✓Deep codebase context via Sourcegraph's Code Search API, pulling relevant symbols and usage patterns across entire codebases for more accurate suggestions
  • ✓Multi-LLM support lets users choose between Claude, GPT-4o, Gemini and other models, and enterprise customers can bring their own keys
  • ✓Wide IDE coverage including VS Code, JetBrains, Visual Studio (experimental), a web interface in the Sourcegraph platform, and CLI access
  • ✓Strong fit for large monorepos and polyrepo enterprise environments where cross-repository context is critical for accurate AI assistance
  • ✓Customizable prompts and commands let teams encode standardized workflows (test generation, code review checklists, documentation) as reusable templates
  • ✓Enterprise-grade governance with SSO, audit logs, repo permission-aware context, and guardrails for compliance-sensitive industries

Cons

  • ✗Full enterprise context features require deploying and configuring Sourcegraph's code intelligence platform, which adds operational overhead
  • ✗Free tier usage limits are more restrictive than some competitors like GitHub Copilot's free offering
  • ✗Maximum value requires proper codebase indexing setup — context quality scales with indexing completeness
  • ✗Smaller extension marketplace compared to GitHub Copilot's broader third-party integration ecosystem
  • ✗Amp (the agentic evolution) is a separate product requiring additional onboarding and different workflows from the core Cody experience
  • ✗Enterprise deployment complexity can be significant for smaller teams without dedicated DevOps resources
  • ✗Learning curve to leverage advanced features like custom prompts, context filters, and @-mentions effectively

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