Cursor vs Devin

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

Cursor

🔴Developer

AI Development Assistants

AI-first code editor with autonomous coding capabilities. Understands your codebase and writes code collaboratively with you.

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Starting Price

Free

🟡Low Code

AI Development Assistants

AI software engineer that codes, fixes bugs, and ships features autonomously. Builds full applications end-to-end with minimal supervision.

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Starting Price

$500/mo

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✓Deep codebase indexing means AI suggestions and agent actions reference real code across the entire repository, not just the open file
✓Tab autocomplete predicts multi-line and multi-file edits with unusually high accuracy, often catching the developer's next intent
✓Agents can run in the editor, cloud, CLI, or mobile, so long tasks don't block local work and can be checked in from anywhere
✓Built on VS Code, so existing extensions, keybindings, themes, and muscle memory transfer with almost no learning curve
✓Cursor Rules let teams encode conventions and architectural constraints that the AI follows consistently across the codebase
✓Access to frontier models from Anthropic, OpenAI, Google, and xAI with per-task model switching and automatic routing

✗Heavy AI usage burns through monthly request quotas quickly, pushing many serious users toward higher-tier plans
✗Performance can degrade on very large monorepos during initial indexing or when many parallel agents are running
✗Being a VS Code fork means it lags slightly behind upstream VS Code releases and occasionally breaks niche extensions
✗Agent autonomy can produce confidently wrong multi-file changes that are tedious to unwind without disciplined version control
✗Privacy-conscious teams must explicitly enable privacy mode and review enterprise terms before sending proprietary code to model providers

✓Operates fully autonomously in a sandboxed VM with shell, browser, and editor access — handles end-to-end tasks that pair-programming tools cannot
✓Integrates directly into existing engineering workflows via Slack, GitHub, Linear, and Jira, so tickets can be assigned to Devin like a human teammate
✓Sessions are observable and interruptible — you can watch its plan, give mid-run feedback, edit files, or rewind to a checkpoint
✓Strong fit for parallelizable backlog work: small bug fixes, test writing, dependency upgrades, and codebase migrations across many files
✓Enterprise-ready with SOC 2 compliance, VPC/self-hosted deployment options, and a Devin API for programmatic dispatch from CI or internal tools
✓Maintains a custom knowledge base of repo conventions, runbooks, and prior decisions so it improves at your codebase over time

✗Significantly more expensive than IDE-based copilots, with usage-based ACU pricing that can escalate quickly on long or complex tasks
✗Quality drops sharply on ambiguous, novel, or architecturally complex work — best results require well-scoped tickets and good documentation
✗Async cloud-VM model means iteration latency is much slower than an inline assistant like Cursor or Copilot for quick edits
✗Requires real human review on every PR — unsupervised merging is risky, so it adds review load even as it removes implementation load
✗Onboarding to a new codebase takes time and tuning of the knowledge base before output quality becomes consistently useful

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