What are ACUs and how are they consumed?

ACUs (Agentic Compute Units) are a normalized measure of the resources Devin uses: VM time, model inference, and networking. One ACU represents roughly 15 minutes of active autonomous work. Consumption varies based on task complexity, codebase size, and prompt specificity.

What is the difference between Pro and Max plans?

Pro ($20/month) includes a standard usage quota with access to frontier models. Max ($200/month) offers significantly higher quotas for power users. Both include Devin Desktop, Tab, and cloud agents, but Max provides more concurrent sessions and priority access.

Can I use Devin for large-scale code migrations?

Yes, Devin is particularly effective for repetitive migration tasks, as demonstrated by Nubank's ETL migration where parallel Devin sessions reduced an 18-month project into weeks.

Who owns the code generated by Devin?

The customer retains full ownership of all inputs, outputs, and generated code regardless of plan. Cognition treats everything as customer intellectual property.

What happens if I exceed my usage limit?

Most users stay within their included quota. If exceeded, you can purchase extra usage in predefined increments (e.g., $120 for 1000 credits on Teams). Plans can auto-reload or be manually topped up.

How does Devin pricing compare to human developers?

For repetitive, high-volume tasks like migrations, ACU costs can be significantly lower than fully-loaded engineer hourly rates. However, for complex feature work requiring heavy human review, the ROI depends on task scoping and quality requirements.

Directory/Coding/AI Assistants/Devin

Devin

Devin is the first autonomous AI software engineer, developed by Cognition AI. It independently plans, writes, tests, and ships production code across your codebase, integrating with your existing development tools. It leverages multiple AI models (including OpenAI, Claude, and Gemini) and operates through a desktop application or cloud agents, enabling it to handle complex tasks such as large-scale migrations, feature implementation, and debugging. Devin is designed for software developers and engineering teams who want to boost productivity by automating repetitive engineering work. By taking over routine coding and testing tasks, Devin allows engineers to focus on higher-level architecture, system design, and creative problem-solving, making it a powerful collaborator in the software development lifecycle.

Coding

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Added on

Jul 9, 2026

Monthly Visits

3.2M

Autonomous codingMulti-model accessVPC deploymentTeam collaborationACU billingSWE models

Product information

Everything worth knowing about Devin

The complete picture — from everyday features to the technical detail builders and IT folks dig for.

Core features

What it actually does

Autonomous Software Engineering

Devin plans, writes, tests, and deploys production code independently, functioning within your existing codebase and toolchain.

Multi-Model Orchestration

Access and orchestrate leading frontier models (OpenAI, Claude, Gemini) and open-source models (like SWE 1.7, Kimi K2.5) for different task complexities.

Collaborative Team Features

Teams plan includes unlimited members, shared workspaces, centralized billing, admin dashboards, and analytics for organizational use.

Enterprise-Grade Security & Deployment

Deploy within your Virtual Private Cloud (VPC) with SAML/OIDC SSO, centralized admin controls, teamspace isolation, and dedicated infrastructure.

Technical capabilities

Agent Compute Units (ACUs) Billing

Usage is billed via ACUs, a normalized measure of compute (VM time, model inference, networking). One ACU ≈ 15 minutes of active agent work.

Proprietary SWE Model Series

Leverages Cognition's own specialized large language models (e.g., SWE-1.7, SWE-1.6) fine-tuned for code generation, planning, and software engineering tasks.

Must watch videos

Devin AI Is the Future of Coding… Full Tutorial

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Tutorial38:06

Devin AI Is the Future of Coding… Full Tutorial

Get started with Devin for free here: https://devin.ai Most AI coding tools still run on your machine. Devin is different — it's a full cloud-based software engineer that works completely independently, so you can hand it a task, close your laptop, and come back to a finished pull request. I'll walk you through every part of the Devin ecosystem — including their new terminal agent, the cloud agent, and the review tool — and show you how to actually use them together in a real dev workflow. Want to make real money with coding? I share high-signal insights on careers, monetization, and leverage in my free newsletter. Join here and get my guide How to Make Money With Coding instantly: https://techwithtim.net/newsletter 🚀 Tools I Use Get 10% off with code techwithtim Openclaw setup: https://www.hostinger.com/techwithtim VPS setup: https://www.hostinger.com/techwithtim10 Wispr Flow (Best AI Dictation): https://ref.wisprflow.ai/techwithtim 🎞 Video Resources 🎞 CLI Install: https://cli.devin.ai/docs#windows SWE1.6 Model: https://cognition.ai/blog/swe-1-6https://cognition.ai/blog/swe-1-6 CLI Docs: https://cli.devin.ai/docs ⏳ Timestamps ⏳ 00:00 | What is Devin AI 01:41 | Devin for Terminal 03:42 | Basic CLI Usage 05:29 | Using Devin in an IDE 08:33 | Permission Modes 10:12 | Memory 11:14 | Models 13:38 | SWE 1.6 Model 15:11 | Session Management 17:26 | Agents.MD 21:10 | Subagents 26:51 | Handing Off to Cloud 30:20 | Devin PR Review 32:55 | Cloud Secrets & Environment 34:08 | Scheduled Tasks 34:32 | GitHub and Slack Integration 35:13 | Linear Integration Demo Hashtags #DevinAI #AICoding #GitHubIntegration UAE Media License Number: 3635141

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Introducing Devin Desktop

Manage fleets of local and cloud agents from one surface. Plan, delegate, review, and ship without leaving your editor. Try it out today: https://devin.ai/desktop

Introducing Devin, the first AI software engineer

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Tutorial1:50

Introducing Devin, the first AI software engineer

Meet Devin, the world’s first fully autonomous AI software engineer.‍ Devin is a tireless, skilled teammate, equally ready to build alongside you or independently complete tasks for you to review. With Devin, engineers can focus on more interesting problems and engineering teams can strive for more ambitious goals. Learn more about Devin and Cognition at https://www.cognition-labs.com/blog and follow us on Twitter at https://twitter.com/cognition_labs

Who uses it

Real use cases, no hype

Code Migration

Automate large-scale codebase migrations and refactoring across thousands of files.

Test Generation

Generate unit tests, integration tests, and improve coverage autonomously.

Dependency Updates

Update package dependencies and fix breaking changes across the codebase.

Bug Fixing

Identify and fix bugs by analyzing code and running tests.

Code Review

Review pull requests for issues and suggest improvements automatically.

Documentation

Create and update documentation from code comments and changes.

Feature Development

Implement new features end-to-end with planning and testing.

What's great

First autonomous AI software engineer
Plans, writes, tests, and ships code independently
Integrates with existing tools like GitHub, Slack, Jira
Unlimited users on all paid plans
Code ownership guaranteed regardless of plan

Technical strengths

Pay-as-you-go with ACU units, no per-seat licensing
Supports parallel sessions for large-scale migrations

Where it falls short

Pricing model based on ACUs can be hard to predict
Not cost-effective for small, less repetitive tasks
Requires clear task scoping to avoid high ACU consumption
Complex open-ended feature development still needs heavy human involvement
Some features (Ask Devin, DeepWiki, Devin Review) now billed separately
Documentation can be scattered and confusing across multiple sites

Technical limitations

ACU consumption varies wildly based on codebase size and complexity

For technical folks

The deep-dive specs

Core Architecture

Orchestrator-based autonomous agent system with specialized planning, code execution, and self-correction loops.

Primary Models

Proprietary SWE series (e.g., SWE-1.7, SWE-1.6), plus integrated frontier models (GPT-4o, Claude 3.5 Sonnet, Gemini 2.0) and open-source models.

Billing Unit

Agent Compute Units (ACUs), representing normalized compute, model inference, and VM runtime.

Deployment Options

SaaS (Cloud), Desktop app, or dedicated Enterprise VPC deployment with full infrastructure isolation.

Integration & Tooling

GitHub, GitLab, Bitbucket, Slack, Microsoft Teams, Linear, Jira, custom git providers, and API access.

FAQ

Includes technical Q&A

Devin uses a consumption-based model with Agentic Compute Units (ACUs). Each plan includes a recurring usage allowance that resets. Additional usage beyond the allowance is billed at published rates.