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Devin

Devin

Fully autonomous AI software engineer

$20/mo Core + $2.25/ACU usage ✓ Strong Consensus Visit Website ↗

Score Breakdown

8.1
8.2
8.6
Task Autonomy 9.1
9.0 9.1 9.3
Accuracy & Reliability 8.0
7.8 7.9 8.3
Speed & Performance 7.9
7.8 7.7 8.1
Tool Integration 8.5
8.5 8.4 8.6
Safety & Guardrails 7.8
7.6 7.8 7.9
Cost Efficiency 8.4
8.4 8.0 8.8
Ease of Use 8.2
8.0 8.3 8.2
Multi-step Reasoning 8.8
8.7 8.7 9.0

Judge Opinions

Claude Opus 8.1

"Devin 2.0's $20/mo price point (down from $500) was a bold move, but independent evaluations tell a mixed story — one test showed only 3 of 20 tasks completed successfully, while Cognition claims 83% improvement per ACU. The truth likely lies between: Devin handles well-scoped migrations and bulk refactoring effectively, but struggles with ambiguous or architecturally complex tasks. ACU costs can spike unpredictably on difficult problems."

+ Highest task autonomy of any coding agent for well-scoped, clearly defined tasks
+ Dramatic $500→$20/mo price reduction makes autonomous coding accessible to individuals
+ Persistent development environment with terminal, browser, and editor maintains context
+ Best-in-class for migrations, bulk refactoring, and clearly defined GitHub issues
- Independent testing shows inconsistent success rates — as low as 15% on diverse task sets
- Can pursue suboptimal approaches for extended periods, wasting ACUs before self-correcting
- ACU-based pricing makes costs unpredictable — difficult problems consume resources quickly
- Rarely asks clarifying questions, preferring to assume — often incorrectly on ambiguous tasks
GPT-5.2 8.2

"Devin is a cloud-hosted autonomous coding agent that can take a ticket, work in a full dev environment (editor/terminal/browser), and deliver a PR with minimal supervision. It’s most valuable when tasks are well-scoped, but success rate and compute usage can vary on messy codebases, so you’ll want strong tests and clear acceptance criteria."

+ High autonomy: can plan, implement, and iterate on tests with minimal prompting
+ Persistent cloud environment with terminal and browser for end-to-end work
+ Good fit for migrations, dependency upgrades, and clearly defined issues
+ Async execution lets you hand off work and review results later
+ Integrates cleanly with GitHub workflows to produce PR-ready changes
- Compute-unit limits and overages can make costs unpredictable on hard tasks
- Can pursue a wrong approach for too long without asking clarifying questions
- Quality varies by repo and task; still needs careful code review and tests
- Remote agent loops can feel slow compared to local iterative editing
Gemini 3 8.6

"Devin's architecture is technically impressive — it maintains a persistent development environment with proper state management across long coding sessions. The planning and decomposition capabilities are best-in-class for coding agents. The main technical weakness is in architectural reasoning, where it sometimes makes choices that a senior engineer would not."

+ Best-in-class task decomposition for complex coding projects
+ Persistent development environment maintains context across sessions
+ Strong codebase understanding through static and dynamic analysis
+ Effective iterative debugging with test-driven approach
- Architectural decision-making lags behind its implementation capabilities
- Resource consumption can be unpredictable on complex problems
- Limited ability to ask clarifying questions — sometimes assumes incorrectly

/// RECOMMENDED_USE_CASE

"Teams looking to offload routine development tasks to a fully autonomous AI engineer that works independently"

Appears In

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