Amp vs Cursor

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

Amp

AI coding assistant

Amp is Sourcegraph’s frontier coding agent for professional developers who want CLI-first automation, long-running agent workflows, MCP-connected tooling, plugins, and pay-as-you-go individual pricing. It is better suited to serious engineering teams than casual coding help because its value depends on terminal workflows, workspace policy, and agent supervision.

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Starting Price

Custom

Cursor

🔴Developer

AI code editor

Cursor is a ai code editor focused on daily software development, large-codebase navigation.

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Starting Price

Custom

Feature Comparison

Scroll horizontally to compare details.

FeatureAmpCursor
CategoryAI coding assistantAI code editor
Pricing Plans6 tiers192 tiers
Starting Price
Key Features
  • CLI-first agent workflow
  • Web, CLI, and mobile agent control
  • Plugin system for events, tools, and workspace policy
  • AI code editor with agent requests and Tab completions
  • Cloud agents plus terminal, Slack, and GitHub workflows
  • MCPs, skills, hooks, and frontier model access on paid plans

💡 Our Take

Choose Amp if your workflow centers on terminal-launched agents, long-running tasks, plugins, and remote control across web, CLI, and mobile. Choose Cursor if your team wants an AI-native editor experience with code assistance embedded directly in the IDE and less emphasis on CLI-first agent orchestration.

Amp - Pros & Cons

Pros

  • Amp supports CLI-first agent workflows and can be installed on Mac, Linux, WSL, Windows, or through Homebrew, which fits developers who live in terminal-based workflows.
  • The June 4, 2026 "Agents, Everywhere" release adds continuity across web, CLI, and mobile so developers can watch and drive agents from more than one surface.
  • Performance claims are specific: Amp says deep and rush modes now receive the first token 87% faster, entire responses are 32% faster at p50, and long-horizon tasks can reach up to a 40% end-to-end speedup.
  • Plugin extensibility is deeper than simple settings: plugins can hook into events, add tools, standardize policy, and be deployed to a workspace.
  • The public pricing message is unusually direct for this category: individuals and non-enterprise workspaces pay pass-through provider API costs with zero markup, no subscription or commitment, and a $5 minimum credit purchase.
  • Team controls include passkey-authenticated "sudo" sessions for web and mobile remote control, which is useful when organizations need stronger governance around agent actions.

Cons

  • Amp does not publish a simple fixed monthly or annual seat price, so teams must estimate usage from provider API costs and Amp credit consumption rather than a flat subscription.
  • Usage-based pricing can be harder to forecast than a flat per-seat subscription, especially for developers running long deep or rush sessions.
  • Amp is aimed at professional developers and software teams; nontechnical users will get little value from its CLI, TUI, plugin, and workspace concepts.
  • The product messaging emphasizes moving quickly with frontier models, which may be uncomfortable for teams that prefer slow-changing, highly standardized tooling.
  • Because Amp is newer and more agent-focused than mainstream editor assistants, teams may need to validate its behavior, permissions, and cost controls before replacing incumbent tools.

Cursor - Pros & Cons

Pros

  • Combines autocomplete, chat, and agent workflows in one polished editor
  • Strong fit for developers who want AI features always available, not bolted on
  • Codebase awareness is more useful than generic chat for existing repositories
  • MCP support gives a path to connect docs, tools, or internal services

Cons

  • Pricing could not be verified by curl during this run; confirm current Pro, team, and usage limits before purchase
  • Editor migration can be a blocker for teams standardized on another IDE
  • Agent edits still require review; generated code can introduce subtle architecture or security issues
  • Heavy AI use may create cost and governance questions for larger engineering teams

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