Devin vs Magic
Two Coding AI tools, side by side. Both are verified against their own live sites. Here is what each does well and who it is for, so you can choose what fits.
Devin
www.devin.ai
An autonomous AI software engineer
Best forEngineering teams handling large, complex, multi-repository projects and modernizations
What it doesDevin, by Cognition, is an autonomous AI software engineer available via cloud, desktop, and CLI. It handles tasks such as code migrations, refactors, pull request review, bug fixing, and documentation, and integrates with tools like GitHub, Linear, and Slack.
Capabilities
Visit Devin →- Code migrations and large-scale refactors
- Pull request review and visual QA
- Bug fixing and incident resolution
- Integrations with GitHub, Linear, Slack and Datadog
- Learns codebases over time
Magic
www.magic.dev
Frontier code models to automate software engineering
Best forOrganizations exploring frontier models for large-context code automation
What it doesMagic builds frontier code models aimed at automating software engineering and research. Its approach combines frontier-scale pre-training, domain-specific reinforcement learning for code, and ultra-long context windows for handling large codebases and complex problems.
Capabilities
Visit Magic →- Frontier code models
- Domain-specific reinforcement learning
- Ultra-long context windows
- Inference-time compute optimization
How to choose
Choose Devin if you are engineering teams handling large, complex, multi-repository projects and modernizations. Choose Magic if you are organizations exploring frontier models for large-context code automation. Both sit in Coding; the right pick depends on your exact workflow and budget.
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