Magic.dev Freemium

Magic.dev is an AI coding agent whose models hold up to 100 million tokens of context, letting it reason across a complete codebase rather than a few open files.

What is Magic.dev?

Magic.dev is an AI coding assistant built around extremely long context. Its models are designed to hold a hundred million tokens at once, which means the agent can keep your entire repository in view rather than guessing from three open files.

You can find it at Magic.dev.

Magic.dev Product Features

• 100M-token context — the LTM-2 model family is built for repository-scale input, not file-scale.
• Agentic task execution — it plans a change, edits files, runs the build and iterates on failures.
• IDE integration — a VS Code and JetBrains surface for everyday editing alongside the autonomous agent.
• Repository indexing — it builds a persistent map of your code so repeated questions do not re-read everything.
• Review assistance — draft pull requests get flagged for missing tests or inconsistent patterns.
• Enterprise deployment — on-premise and VPC options for teams that cannot send code to a public API.

Product Highlights

• Free tier available for individual developers; paid plans are quoted per seat for teams.
• Backed by major investors and positioned as a frontier-model lab, not just an editor plugin.
• Enterprise contracts include dedicated support and deployment options.

Magic.dev Use Cases

• Refactoring a pattern that appears in hundreds of files across a monorepo.
• Answering ‘where is this feature implemented?’ without grep archaeology.
• Auditing a codebase for a deprecated API before a framework upgrade.
• Generating migration plans that account for modules you forgot existed.
• Reviewing large pull requests that no human reviewer wants to read fully.

Who should use Magic.dev?

Good fit: For genuinely large codebases, context length beats clever retrieval. Teams with a legacy monolith often find this more useful than faster but shallower agents, and enterprise deployment options matter for regulated industries.

Where it falls short: Long-context inference is slow and expensive, so simple edits feel heavier than in Cursor or Copilot. Public pricing is opaque, and the product is less mature than the incumbents on polish.

Bottom line: Worth evaluating if you work in a vast codebase and can tolerate slower turns. For everyday editing, Cursor or GitHub Copilot will feel snappier.

Quick Summary

• Magic.dev is a US AI lab building long-context coding models, founded in 2022.
• Its headline claim is a 100-million-token context window on the LTM model family.
• Free tier exists for individuals; team pricing is quote-based.
• It competes on context length rather than raw benchmark scores.
• The trade-off is speed — huge context costs latency and money per request.