Claude Code vs Devin: Which AI Tool is Better?

Last updated: 2026

Claude Code logo

Claude Code

From $20/mo

Devin logo

Devin

Free plan available

Side-by-Side Comparison

Claude CodeDevin
Rating
Starting Price$20/mo$500/mo
Free Plan
Categoryai-codeai-code
Top Features
  • Autonomous multi-step coding agent - runs in your terminal
  • Reads entire codebases and edits across multiple files
  • Runs shell commands, tests, and build steps autonomously
  • GitHub integration - create and merge PRs
  • Autonomous end-to-end task execution from issue to pull request
  • Isolated sandbox with shell, browser, and editor
  • GitHub integration - reads issues, opens PRs
  • Reads documentation and external websites autonomously
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Claude Code and Devin are both autonomous AI coding agents that can handle multi-step software engineering tasks, making this one of the more direct comparisons in the AI coding space. Both run in development environments and can complete tasks without constant supervision. The key differences are price, scope of autonomy, and who they are designed for.

Claude Code

Claude Code is Anthropic's autonomous coding agent, running in your terminal. You give it a task - fix a bug, build a feature, write tests - and it reads your codebase, edits files, runs commands, and creates commits and PRs autonomously. It uses Claude's models and requires Claude Pro at $20/mo or API access with token-based costs that scale with task complexity. It is a tool for individual developers and small teams who want agentic coding capabilities at a significantly lower price than enterprise-tier agents.

Devin

Devin operates in a fully isolated sandbox with a shell, browser, and editor. It reads GitHub issues, writes and tests code across files, browses the web for documentation and context, and opens pull requests - all autonomously from a single task description. At $500/mo, it is priced for engineering teams rather than individual developers. Devin is positioned as an AI team member that can work on tasks in parallel with human engineers.

Key Differences

  • Price: Claude Code starts at $20/mo; Devin starts at $500/mo. A 25x cost difference for broadly similar autonomous capability.
  • Environment: Devin has a fully isolated sandbox with browser access. Claude Code runs in your local terminal.
  • Web browsing: Devin can browse documentation and external resources during task execution. Claude Code does not browse the web.
  • Target audience: Claude Code targets individual developers. Devin targets engineering teams with enterprise budgets.
  • GitHub integration: Both read issues and open PRs. Devin's GitHub integration is more fully featured.

Pricing

Claude Code requires Claude Pro at $20/mo or API access with per-token costs. Devin starts at $500/mo.

Who Each Is For

Claude Code suits individual developers and small teams who want autonomous agentic coding capabilities at a reasonable price point, running in their existing terminal environment.

Devin suits enterprise engineering teams with the budget for a fully isolated AI software engineer that can work alongside human engineers on complete tasks with web research capability.

Claude Code Pros & Cons

👍 Pros

  • Handles complete multi-file tasks autonomously
  • Works with any editor - no plugin required
  • Built by Anthropic on Claude's strong reasoning capabilities
  • GitHub integration for end-to-end PR workflows

👎 Cons

  • No free tier - requires Pro or API subscription
  • Token costs accumulate fast on large agentic tasks
  • Terminal-only - no GUI
  • Requires comfort with terminal-based workflows

Devin Pros & Cons

👍 Pros

  • Genuinely handles full tasks end-to-end without supervision
  • Can read documentation and navigate the web as part of a task
  • Opens complete, tested pull requests
  • Good for well-scoped tickets a junior engineer would handle

👎 Cons

  • Expensive at $500/month - hard to justify for individuals
  • Struggles with ambiguous or architecturally complex tasks
  • Slower than doing simple tasks manually
  • Requires clear, well-scoped task definitions for best results

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