Devin

Devin

Cognition AI
SWE-2

SWE-2

Cognition
+
+

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About

Devin is an AI-driven software development assistant designed to collaborate with engineering teams to automate and accelerate coding tasks. It helps with tasks like setting up repositories, writing code, debugging, and performing migrations, all while working autonomously or alongside human developers. Devin is capable of learning from examples, making it more efficient over time. Its use has led to significant time and cost savings in large-scale projects, as seen in its deployment at Nubank, where it delivered 8-12x faster migrations and reduced costs by over 20x. Devin is particularly useful in refactoring and automating repetitive engineering tasks.

About

SWE-2 is Cognition’s advanced coding model designed to improve software engineering performance while reducing the cost of agentic coding workflows. The model is post-trained from Kimi K3 and uses reinforcement learning to optimize multiple reasoning-effort levels within a single training run. SWE-2 is designed to explore codebases more selectively, begin implementation sooner, and complete tasks with fewer redundant reads and reasoning steps than earlier Cognition models. Its capabilities include code generation, debugging, test creation, verification, repository analysis, and complex terminal-based software engineering tasks. The model also emphasizes stronger engineering judgment, end-to-end test coverage, instruction following, and evidence-based verification of user assumptions. SWE-2 is available through Devin Desktop and Devin CLI, with broader rollout planned across Devin Web and Fusion.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Software development teams and engineers looking for an AI-powered assistant to automate coding tasks, improve project efficiency, and reduce costs

Audience

Software developers, engineering teams, AI coding agent users, DevOps professionals, and organizations that need capable agentic software engineering with lower execution cost and more efficient reasoning

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

$20/month
Pro: $20/month
Max: $200/month
Free Version
Free Trial

Pricing

$20/month
Free Version
Free Trial

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 4.0 / 5
design 4.0 / 5
support 4.0 / 5

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 5.0 / 5

Pros & Cons from Real Users

Pros

  • I’ve found Devin to be an incredible tool for streamlining my coding process. It delivers quick and accurate code suggestions, which have really helped me reduce development time. Whether I’m tackling complex algorithms or debugging, Devin’s responses are always precise and helpful. The integration into my coding environments has been seamless, and it consistently understands the context of the project, even with minimal input.

Cons

  • While Devin is great for most coding tasks, I’ve noticed it struggles a bit with more abstract problems that require creative or unconventional solutions. Its suggestions tend to be based on patterns, which sometimes miss the mark when working on unique or highly specialized projects. Additionally, it occasionally over-explains simple solutions, making the responses longer than necessary.

Pros & Cons from Real Users

Pros

  • The biggest thing that stands out is the cost-performance balance. SWE-2 is not just trying to top one benchmark; it is trying to get very close to frontier coding performance at a much lower cost. For developers, that matters a lot. Coding agents can burn through tokens quickly when they are reading files, making edits, running tests, and iterating. A model that performs near the top while being meaningfully cheaper is much easier to use every day. I also like that SWE-2 seems built for real software engineering workflows, not just isolated code snippets. The strong DeepSWE and Terminal-Bench results make it especially interesting for repo-level tasks, debugging, tool use, and longer agent runs.

Cons

  • Benchmarks are useful, but real projects bring messy architecture, flaky tests, undocumented behavior, and weird edge cases.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Cognition AI
Founded: 2023
United States
devin.ai/

Company Information

Cognition
Founded: 2023
United States
cognition.com

Alternatives

Amp

Amp

Amp Code

Alternatives

Devin Desktop

Devin Desktop

Cognition
Claude Code

Claude Code

Anthropic
GPT-5.6 Sol

GPT-5.6 Sol

OpenAI
Goose

Goose

Block
SWE-1.7

SWE-1.7

Cognition
SWE-1.6

SWE-1.6

Cognition

Categories

Categories

Integrations

C
C#
C++
CSS
Devin Desktop
Go
HTML
JavaScript
Kotlin
Lua
MATLAB
PHP
Python
R
Rust
SQL
Swift
TypeScript
Assembly
GPT-5.4 nano

Integrations

C
C#
C++
CSS
Devin Desktop
Go
HTML
JavaScript
Kotlin
Lua
MATLAB
PHP
Python
R
Rust
SQL
Swift
TypeScript
Assembly
GPT-5.4 nano
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