Magic vs Cody
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.
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
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
Visit Cody →- Chat with repository context
- Auto-edit contextual code changes
- Customizable and premade prompts
- Context filters for repositories
How to choose
Choose Magic if you are organizations exploring frontier models for large-context code automation. Choose Cody if you are developers and teams who want code assistance grounded in their full codebase context. Both sit in Coding; the right pick depends on your exact workflow and budget.
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