AI WikiAI Wiki
Zed logo

Zed

Free tier

Your last next editor

Free tier available·All audiences·Powered by Multiple (Anthropic Claude, OpenAI, Google, and others; own Zeta2 model for edit prediction)·Open source
Visit

Key strengths

Speed (written in Rust, leverages multiple CPU cores and GPU)Agentic/AI editing with parallel agentsReal-time collaboration (chat, co-editing, screen sharing)Native Git supportEdit prediction via open-weight Zeta2 modelDebugger via DAPRemote developmentMultibuffer editingVim-friendly modal editing
Free tier + paid plans · from $10 USD/mo
No ratings yet

Zed — Technical Use Cases

  • High-throughput solo development: Rust-based architecture with GPU/multi-core rendering makes Zed suitable for developers working in large codebases where editor latency is a bottleneck.
  • AI-augmented workflows with model flexibility: Teams can route edit predictions through Zed's hosted Zeta2 model or plug in their own Anthropic, OpenAI, or Google API keys — enabling cost control and model selection per project.
  • Parallel agentic coding: Zed supports running multiple AI agents concurrently, making it a strong fit for workflows that delegate subtasks (e.g., test generation, refactoring, documentation) to separate agents simultaneously.
  • Remote development: Developers working on cloud VMs or remote servers can use Zed's remote development support to edit and run code on distant machines without leaving the editor.
  • Distributed engineering teams: Real-time co-editing, in-editor chat, and screen sharing reduce the need for external collaboration tools during pair programming or code review sessions.
  • Debugger-integrated development: DAP support means Zed can serve as a full development environment for languages with DAP-compatible debug adapters, reducing context switching.
  • Vim-native developers: Modal editing support lets keyboard-driven developers adopt Zed without abandoning their muscle memory.
  • Cross-file refactoring: Multibuffer editing enables engineers to view and edit across multiple files in a single unified surface — useful for large-scale refactors.