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Magic.dev

Autonomous AI engineer trained on long contexts — handles hour-long coding sessions without losing track.

B67💻CodeAutonomousSubscription
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Agent Rank breakdown

Agent Rank
67/ 100
BB-tier
Autonomy fit
9
Capabilities
6
Integrations
2
Pricing value
9
Polish & maturity
4
Verifiability
10

Auto-computed from autonomy, capabilities, integrations, pricing, maturity and editorial verification. Updated every deploy. How is this computed?

Capabilities

  • Code
  • Tool use
  • Memory

Integrations

Version control
GitHubGitLab

Pricing tiers

Enterprise
Custom
Engineering teams
  • +Long-context model (100M+ tokens)
  • +Codebase-wide reasoning
  • +Custom deployment
Want the real monthly cost at your volume? Use the TCO calculator →

Pros & cons

Pros
  • +Unique long-context model — can hold an entire mid-sized repo in one session
  • +Strong on cross-cutting refactors that other agents struggle with
  • +Funded at frontier-lab levels — engineering muscle behind the product
Cons
  • −Enterprise pricing — no public per-seat tier
  • −Newer entrant — fewer customer references than Devin or Cursor
  • −Best for very large codebases; overkill for solo + small-team work
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