Magic vs Cody

Two Coding AI tools, side by side. Both are checked against their own published sites at time of listing. This comparison is editorially independent — neither tool has reviewed or endorsed this page. Here is what each does well and who it is for, so you can choose what fits.

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

• Frontier code models
• Domain-specific reinforcement learning
• Ultra-long context windows
• Inference-time compute optimization

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Cody

sourcegraph.com

AI coding assistant that uses development context to write and fix code

Best forDevelopers and teams who want code assistance grounded in their full codebase context.

What it doesCody is an AI coding assistant from Sourcegraph that uses current models together with codebase context to help developers understand, write, and fix code. It pulls context through Sourcegraph's search to surface APIs, symbols, and usage patterns across a codebase. It works in VS Code, JetBrains, Visual Studio, and a web app.

Capabilities

• Chat with repository context
• Auto-edit contextual code changes
• Customizable and premade prompts
• Context filters for repositories

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