Zed Editor: The Fastest AI-Powered Editor (2026)

Posted: April 14, 2026 to Technology.

Zed is a high-performance code editor built from scratch in Rust by the team that created Atom and Tree-sitter. It uses GPU-accelerated rendering through a custom framework called GPUI, delivers sub-millisecond input latency, and includes a built-in AI assistant that supports Claude, GPT-4, and local models. If you have been waiting for an editor that combines the speed of a terminal-based tool with the features of a modern IDE, Zed is the strongest candidate in 2026. This guide covers installation, configuration, AI integration, and practical workflows for AI development and cybersecurity work.

At Petronella Technology Group, our engineering team evaluates development tools continuously. We switched several workstations to Zed for AI and security development after benchmarking it against VS Code, Cursor, and Neovim. We wrote this guide because Zed takes a fundamentally different approach to editor architecture, and understanding that architecture is key to getting the most from it.

What Is Zed and Why It Exists

Zed was created by Nathan Sobo, the original creator of Atom, along with key members of the Atom and Tree-sitter teams. After GitHub discontinued Atom in 2022, the team took everything they learned from building one of the most popular editors in history and started over with a clean slate. The goal was not to build Atom 2.0. It was to build the fastest graphical code editor possible while incorporating AI assistance as a first-class feature rather than an afterthought.

The decision to write Zed in Rust was deliberate. Atom was built on Electron, which meant every keystroke traveled through layers of JavaScript and Chromium rendering. That architecture made Atom extensible but slow. VS Code improved on Atom's performance by optimizing the Electron layer, but it still carries the overhead of a full web browser runtime. Zed bypasses all of that. It talks directly to the GPU through Metal on macOS and Vulkan on Linux, rendering text and UI elements the same way a video game renders frames. The result is measurable: Zed starts in under 500 milliseconds on a cold boot and processes keystrokes in under one millisecond.

Tree-sitter, the incremental parsing framework that Sobo co-created, is deeply integrated into Zed. Where other editors parse syntax by applying regex patterns line by line, Tree-sitter builds a full syntax tree for the entire file and updates only the changed portions when you edit. This means syntax highlighting, code folding, and structural navigation all remain accurate even in large files with complex nesting. Every editor that uses Tree-sitter benefits from it, but Zed's integration is tighter because the same team built both tools.

Zed went open source in January 2024 under a copyleft license (GPL for the editor, Apache/MIT for the GPUI framework). The company behind Zed sustains itself through Zed's cloud collaboration features and AI services, not by selling the editor itself. This means the core editing experience, including all AI features that use your own API keys, is free and open source.

Why Zed Is Different From Every Other Editor

The editor landscape in 2026 has consolidated around a few architectural approaches. VS Code and its derivatives (including Cursor) run on Electron. JetBrains IDEs run on the JVM. Neovim runs as a terminal application with optional GUI frontends. Zed does none of these. It is a native application that renders through the GPU.

Not Electron, Not a Fork

Zed is not a VS Code fork. It does not use Electron, Chromium, or any web technology for its UI. The entire editor, from the text buffer to the tab bar to the settings panel, is rendered through GPUI, Zed's custom GPU-accelerated UI framework written in Rust. GPUI treats UI elements like game objects: it maintains a scene graph, diffs it between frames, and sends draw calls to the GPU. This eliminates the overhead of DOM layout, CSS cascade, and JavaScript event loops that Electron-based editors carry.

The practical impact is visible immediately. Open a 50,000-line file in VS Code and scroll quickly. You will see frame drops, blank regions, and re-rendering artifacts. Open the same file in Zed and scroll at maximum speed. The rendering remains smooth because the GPU handles the text layout and the CPU is free to process your actual edits.

Sub-Millisecond Input Latency

Input latency is the time between pressing a key and seeing the character appear on screen. In Electron-based editors, this latency typically measures between 30 and 80 milliseconds, depending on extensions, file size, and system load. In Zed, input latency consistently measures under one millisecond. This sounds like a marginal improvement until you type for eight hours. Accumulated latency creates a subtle friction that fatigues your hands and breaks your flow state. Professional typists and developers who switch to Zed consistently report that editing "feels" different, and this is why.

Built-In AI From the Start

Most editors added AI features after the fact. VS Code uses GitHub Copilot as an extension. Neovim relies on community plugins like copilot.vim or cmp-ai. Cursor forked VS Code to add deeper AI integration. Zed built its AI assistant into the editor from the start, which means AI interactions are not limited to autocomplete suggestions. You can open an AI panel for conversational coding, select code and describe a transformation in natural language, use inline completions during typing, and configure project-specific system prompts. Because the AI is native to the editor rather than bolted on through an extension API, it has access to your full project context, open files, and syntax tree.

Installation on macOS and Linux

macOS

Zed has first-class macOS support and uses Metal for GPU rendering. Download from the official site or install via Homebrew:

# Homebrew (recommended)
brew install --cask zed

# Or download directly from https://zed.dev/download

After installation, launch Zed from Applications or run zed from the terminal. On first launch, Zed will prompt you to install the zed CLI command for opening files and projects from the terminal.

Linux

Linux support reached stable status in 2025. Zed uses Vulkan for GPU rendering on Linux, which requires a Vulkan-capable GPU driver. For NVIDIA GPUs, this means driver version 525 or later. AMD and Intel GPUs work through Mesa's Vulkan implementation (RADV and ANV respectively).

# Official installer (recommended)
curl -f https://zed.dev/install.sh | sh

# This installs to ~/.local/bin/zed and adds it to your PATH

On NixOS, Zed is available in nixpkgs:

# configuration.nix or home.nix
environment.systemPackages = with pkgs; [
  zed-editor
];

On Arch Linux:

# Stable release
sudo pacman -S zed

# Or from AUR for nightly builds
yay -S zed-editor-nightly-bin

On Ubuntu and Debian-based distributions:

# Download the .deb package from https://zed.dev/download
# Or use the install script above

After installation on Linux, verify Vulkan support is working:

# Check Vulkan driver
vulkaninfo --summary | head -20

# If Vulkan is missing, install the appropriate driver
# NVIDIA: sudo apt install nvidia-driver-535 (or later)
# AMD: sudo apt install mesa-vulkan-drivers
# Intel: sudo apt install mesa-vulkan-drivers

Key Features Deep Dive

GPU-Accelerated Rendering (GPUI Framework)

GPUI is Zed's custom UI framework and arguably its most significant technical achievement. Traditional desktop UI frameworks (GTK, Qt, Electron) render through the CPU and composite the result. GPUI skips this entirely. It maintains a declarative UI tree in Rust, diffs it between frames, and emits GPU draw calls for only the changed regions. Text rendering uses a glyph atlas cached on the GPU, so even scrolling through thousands of lines involves minimal data transfer between CPU and GPU memory.

For developers working with large files, complex projects, or multiple splits, GPUI means the editor never becomes the bottleneck. Syntax highlighting for a 100,000-line file completes in single-digit milliseconds because Tree-sitter provides the parse tree incrementally and GPUI renders the colored tokens directly on the GPU.

Multi-Buffer Editing

Multi-buffer editing is one of Zed's most distinctive features. When you perform a project-wide search, Zed does not just show you a list of matching files. It renders all matching locations in a single scrollable buffer where you can edit every match in place. Change a function signature across 15 files without opening 15 tabs. The multi-buffer view shows enough context around each match to edit confidently, and your changes apply to the actual files immediately.

This feature also powers Zed's "Find All References" and "Go to Definition" workflows. Instead of jumping between files in separate tabs, you see all relevant locations in one view and navigate between them vertically.

Collaborative Editing

Zed includes real-time collaborative editing similar to Google Docs but for code. Multiple users can open the same project, see each other's cursors, and edit simultaneously. Collaboration is built on CRDTs (Conflict-free Replicated Data Types), the same technology that powers tools like Figma's multiplayer mode. This means edits merge automatically without conflicts, even when two users modify the same line simultaneously.

Collaborative editing runs through Zed's servers by default, but the protocol is part of the open-source codebase. For organizations that need to keep code on their own infrastructure, self-hosted collaboration is on the roadmap. In the meantime, the collaboration channel is encrypted in transit and Zed's servers do not persist your code after the session ends.

Built-In Terminal

Zed's built-in terminal is not an afterthought. It uses the same GPU-accelerated rendering as the editor, which means terminal output renders as fast as editor text. If you run a build command that produces thousands of lines of output, the terminal does not lag behind. For developers who pair their editor with a dedicated terminal emulator like Ghostty, Zed's built-in terminal serves as a convenient secondary terminal for quick commands without switching windows.

Language Server Protocol Support

Zed supports the Language Server Protocol (LSP) for intelligent code features: autocomplete, go-to-definition, find references, rename, diagnostics, and code actions. Language servers start automatically when you open a file of a supported language. Zed ships with built-in support for dozens of languages including Python, Rust, TypeScript, Go, C/C++, Java, and more. Configuration happens in settings.json if you need to point to a specific language server binary or pass custom initialization options.

Tree-sitter Syntax

Every file you open in Zed is parsed by Tree-sitter into a concrete syntax tree. This powers not just syntax highlighting but also code folding, bracket matching, scope detection, and structural selection (select the entire function, the entire block, or the entire argument list with a single command). Tree-sitter grammars are installed automatically per language. Because parsing is incremental, even rapid typing in a large file does not cause a perceptible delay in highlighting updates.

AI Features: Claude, GPT-4, and Local Models

Zed's AI features fall into three categories: the assistant panel for conversational coding, inline transforms for targeted edits, and inline completions for real-time suggestions. All three can be configured to use different AI providers.

Assistant Panel Configuration

The assistant panel is a chat interface embedded in the editor. Open it with Ctrl+Shift+? (Linux) or Cmd+Shift+? (macOS). You can ask questions about your codebase, request code generation, debug errors, or discuss architecture. The assistant has access to your open files and project context, so you can reference specific functions or files in your prompts.

Configure your AI provider in ~/.config/zed/settings.json:

{
  "assistant": {
    "default_model": {
      "provider": "anthropic",
      "model": "claude-sonnet-4-20250514"
    },
    "version": "2"
  },
  "language_models": {
    "anthropic": {
      "api_url": "https://api.anthropic.com",
      "available_models": [
        {
          "name": "claude-sonnet-4-20250514",
          "display_name": "Claude Sonnet 4",
          "max_tokens": 8096,
          "max_output_tokens": 8096
        },
        {
          "name": "claude-opus-4-20250514",
          "display_name": "Claude Opus 4",
          "max_tokens": 8096,
          "max_output_tokens": 8096
        }
      ]
    }
  }
}

You will need to add your Anthropic API key through Zed's settings UI or by setting the ANTHROPIC_API_KEY environment variable before launching Zed.

Connecting GPT-4 as an Alternative Provider

To use OpenAI models instead of or alongside Anthropic:

{
  "language_models": {
    "openai": {
      "api_url": "https://api.openai.com/v1",
      "available_models": [
        {
          "name": "gpt-4o",
          "display_name": "GPT-4o",
          "max_tokens": 128000,
          "max_output_tokens": 4096
        }
      ]
    }
  }
}

You can switch between providers per conversation in the assistant panel. This is useful for comparing model outputs on the same prompt or using different models for different tasks (Claude for nuanced refactoring, GPT-4o for quick utility code).

Using Local Models via Ollama

For organizations that cannot send code to external APIs, Zed supports local models through Ollama. This keeps all AI interactions on your local machine or internal network:

{
  "language_models": {
    "ollama": {
      "api_url": "http://localhost:11434",
      "available_models": [
        {
          "name": "codellama:34b",
          "display_name": "Code Llama 34B",
          "max_tokens": 16384
        },
        {
          "name": "deepseek-coder-v2:latest",
          "display_name": "DeepSeek Coder V2",
          "max_tokens": 32768
        }
      ]
    }
  }
}

Local model quality depends on the model size and your hardware. A 34B parameter model running on an NVIDIA RTX 4090 provides useful code suggestions, though the quality gap compared to Claude or GPT-4 is noticeable for complex refactoring tasks. For organizations handling regulated data where code cannot leave the network, the tradeoff is acceptable. See our AI services overview for guidance on choosing between cloud and local AI deployment.

Inline Transforms

Inline transforms are Zed's most practical AI feature for daily coding. Select a block of code, press Ctrl+Enter, and type a natural language description of the change you want. Zed sends the selected code and your instruction to the AI model and applies the transformation directly in the buffer. You see the diff inline and can accept or reject the changes.

Practical examples of inline transforms:

• Select a function and type "add error handling for network timeouts"
• Select a SQL query and type "convert to parameterized query to prevent SQL injection"
• Select a class and type "add type hints to all methods"
• Select a test and type "add edge cases for empty input and null values"

Inline transforms differ from the assistant panel in an important way: they operate on specific code selections rather than conversational context. This makes them faster for targeted edits. For exploratory work or architectural discussions, the assistant panel is more appropriate.

Custom System Prompts Per Project

Zed supports project-specific system prompts through a .zed/prompts directory at the root of your project. Create markdown files in this directory, and Zed will include their content as system context for all AI interactions within that project:

# .zed/prompts/project-context.md

This project is a Python FastAPI application for cybersecurity assessment automation.
It uses SQLAlchemy for database access, Pydantic for validation, and Celery for
background tasks. All API responses must follow the JSON:API specification.
Security requirements: all user input must be sanitized, all database queries
must use parameterized statements, and all API endpoints require JWT authentication.

This feature is invaluable for team projects. Instead of each developer explaining the project's conventions to the AI every session, the system prompt provides consistent context. New team members get AI assistance that already understands the project's architecture and constraints.

Inline Completions

Zed supports inline code completions powered by AI models, similar to GitHub Copilot. As you type, the editor sends your current context to the configured completion provider and displays ghost text suggestions that you can accept with Tab. Configure completions in settings.json:

{
  "features": {
    "inline_completion_provider": "copilot"
  }
}

Zed supports Copilot, Supermaven, and its own Zed AI completion service. You can also disable inline completions entirely if you prefer to use only the assistant panel and inline transforms for AI interaction.

Configuration and Customization

Settings.json Format

Zed uses JSON for its configuration file at ~/.config/zed/settings.json. Open it directly from Zed with Ctrl+, (Linux) or Cmd+, (macOS). Here is a comprehensive configuration for development work:

{
  "theme": "One Dark",
  "ui_font_size": 15,
  "buffer_font_family": "JetBrains Mono",
  "buffer_font_size": 14,
  "buffer_line_height": {
    "custom": 1.6
  },
  "tab_size": 4,
  "format_on_save": "on",
  "autosave": {
    "after_delay": {
      "milliseconds": 1000
    }
  },
  "soft_wrap": "preferred_line_length",
  "preferred_line_length": 100,
  "show_whitespaces": "boundary",
  "relative_line_numbers": true,
  "cursor_blink": false,
  "scrollbar": {
    "show": "auto"
  },
  "indent_guides": {
    "enabled": true,
    "coloring": "indent_aware"
  },
  "inlay_hints": {
    "enabled": true
  },
  "git": {
    "inline_blame": {
      "enabled": true,
      "delay_ms": 500
    }
  },
  "terminal": {
    "font_family": "JetBrains Mono",
    "font_size": 13,
    "line_height": {
      "custom": 1.4
    },
    "shell": {
      "program": "/usr/bin/fish"
    }
  },
  "vim_mode": true
}

Zed supports per-project settings through a .zed/settings.json file at the project root. This is useful for enforcing team conventions like tab size, formatter, and language server configuration on a per-repository basis.

Keybinding Customization

Keybindings are configured in ~/.config/zed/keymap.json. Zed uses a context system for keybindings, so you can bind the same key to different actions depending on whether you are in the editor, terminal, assistant panel, or file finder:

[
  {
    "context": "Editor",
    "bindings": {
      "ctrl-shift-k": "editor::DeleteLine",
      "ctrl-d": "editor::SelectNext",
      "ctrl-shift-d": "editor::DuplicateLineDown",
      "ctrl-/": "editor::ToggleComments",
      "ctrl-shift-p": "command_palette::Toggle"
    }
  },
  {
    "context": "Terminal",
    "bindings": {
      "ctrl-t": "workspace::NewTerminal",
      "ctrl-shift-t": "terminal_panel::ToggleFocus"
    }
  },
  {
    "context": "Workspace",
    "bindings": {
      "ctrl-b": "workspace::ToggleLeftDock",
      "ctrl-j": "terminal_panel::ToggleFocus",
      "ctrl-shift-e": "project_panel::ToggleFocus"
    }
  }
]

If you are coming from VS Code, Zed includes a VS Code keymap preset that maps most common shortcuts. Enable it in settings:

{
  "base_keymap": "VSCode"
}

Vim Mode

Zed includes a full Vim emulation mode that supports normal, insert, visual, and command modes. It handles motions (ciw, d$, yip), text objects, macros, marks, and registers. Enable it with "vim_mode": true in settings. For developers coming from Neovim, Zed's Vim mode provides a familiar editing model with GPU-accelerated rendering and native AI integration.

Theme and Font Setup

Zed ships with dozens of built-in themes and supports community themes through extensions. Browse and install themes through the extension panel (Ctrl+Shift+X). For font configuration, Zed supports any system-installed font family. Our team uses JetBrains Mono for its ligature support and clear distinction between similar characters (1/l, 0/O). Nerd Fonts variants work as well for icon rendering in the terminal.

Extension Installation

Zed's extension system uses WebAssembly (WASM), which provides sandboxed execution. Extensions cannot access your filesystem or network directly; they communicate through a defined API. Install extensions through the extensions panel or by searching in the command palette. Key extensions for development work include:

• Docker for Dockerfile and compose file support
• TOML for Cargo.toml and pyproject.toml editing
• SQL for database query editing with syntax highlighting
• Nix for NixOS configuration file support
• Terraform for infrastructure-as-code editing
• Markdown for documentation with preview

The extension ecosystem is growing but is significantly smaller than VS Code's marketplace. This is Zed's most frequently cited limitation, and we address it in the limitations section below.

Zed for AI and Machine Learning Development

AI and ML development involves working with large datasets, long-running training scripts, GPU monitoring, and rapid iteration on model configurations. Zed handles several aspects of this workflow particularly well.

Python LSP Integration

Zed uses Pyright as its default Python language server, providing type checking, autocomplete, and diagnostics. For ML projects that use PyTorch, TensorFlow, or JAX, Pyright's type inference handles the complex tensor type signatures that these libraries produce. Configure Python-specific settings in your project's .zed/settings.json:

{
  "languages": {
    "Python": {
      "language_servers": ["pyright"],
      "format_on_save": {
        "external": {
          "command": "ruff",
          "arguments": ["format", "--stdin-filename", "{buffer_path}", "-"]
        }
      },
      "formatter": {
        "external": {
          "command": "ruff",
          "arguments": ["format", "--stdin-filename", "{buffer_path}", "-"]
        }
      }
    }
  }
}

Terminal for GPU Monitoring

ML engineers frequently run nvidia-smi, nvtop, or gpustat to monitor GPU utilization during training. Zed's GPU-accelerated terminal handles the rapid screen updates from monitoring tools without the rendering lag that Electron-based terminals exhibit. Split your editor with code on the left and a terminal running watch -n 1 nvidia-smi on the right without impacting editor performance.

AI Assistant for ML Code

The AI assistant excels at ML-specific tasks when configured with a project system prompt that describes your model architecture, data pipeline, and training infrastructure. Ask it to explain PyTorch autograd behavior, debug CUDA memory errors, convert between data formats, or generate data augmentation pipelines. Because the assistant panel maintains conversation history within a session, you can iteratively refine model code through multiple rounds of discussion.

Multi-Buffer for Configuration Management

ML projects often have configuration scattered across YAML files, Python scripts, and environment files. Use Zed's multi-buffer search to find and update hyperparameters, file paths, or model names across all configuration files simultaneously. Search for learning_rate and edit every occurrence in context without opening each file individually.

Zed for Cybersecurity Work

Cybersecurity professionals work with log files, configuration audits, vulnerability reports, and rapid code review. Zed's performance characteristics make it particularly effective for several security workflows.

Fast Log Analysis

Security log files routinely reach hundreds of megabytes. Zed opens and renders large files significantly faster than VS Code or Cursor because the GPU handles text rendering and Tree-sitter provides immediate syntax highlighting. Open a 200MB Apache access log or a Suricata alert log and search through it without the editor freezing. The search is project-wide by default and returns results in a multi-buffer view where you can examine each match with surrounding context.

Multi-File Search for Configuration Audits

During a configuration audit or CMMC assessment, you need to search across dozens of configuration files for specific settings: password policies in GPO exports, firewall rules in iptables configs, encryption settings in application config files. Zed's project-wide search with multi-buffer editing lets you review all matching configurations in a single scrollable view, annotate findings inline, and track which settings need remediation.

Collaborative Security Auditing

Zed's real-time collaboration features support pair security reviews. Two assessors can open the same project, review different sections of a codebase simultaneously, and see each other's cursors and selections. This is useful during code review for penetration test findings, where one assessor examines the vulnerable code path while another traces the data flow from the entry point. Both see the full context in real time without screen sharing lag.

Vim Mode for Efficiency

Many cybersecurity professionals are Vim users by necessity (SSH into servers, edit configs on remote machines). Zed's Vim mode provides the same keybinding muscle memory in a graphical editor with AI assistance. You can grep through a codebase with /pattern, jump to definitions with gd, and edit with Vim motions while also using the AI assistant to explain unfamiliar code patterns found during a security review.

Performance Comparison: Zed vs VS Code vs Cursor vs Neovim

We benchmarked these editors on an Ubuntu workstation with an AMD Ryzen 9 7950X, 64GB RAM, and NVIDIA RTX 4090. All measurements are averaged over five runs with the same test project (a 15,000-file Python monorepo).

* Neovim input latency depends on terminal emulator. Measured with Ghostty, which itself has GPU-accelerated rendering.

The benchmarks tell a clear story. Neovim is fastest for startup and raw text operations because it runs in a terminal without a GUI layer. Zed is the fastest graphical editor by a significant margin. VS Code and Cursor are functional but carry the weight of Electron. The choice depends on whether you need a graphical interface (Zed) or prefer a terminal-native workflow (Neovim).

Current Limitations and Roadmap

Zed is impressive but it is not without limitations. Being transparent about these helps you decide whether it fits your workflow today or whether you should wait for future releases.

Younger Extension Ecosystem

VS Code has over 50,000 extensions built over a decade. Zed has around 700 as of early 2026. Most common languages and workflows are covered, but niche tools, specific framework integrations, and specialized debugger configurations may not have Zed extensions yet. If your workflow depends on a specific VS Code extension (like a proprietary framework's tooling), verify that Zed has an equivalent before switching. The WASM-based extension system is well-designed and the ecosystem is growing steadily, but it will take time to approach VS Code's breadth.

Linux Support Is Newer

Zed started as macOS-only and added Linux support in 2024. The Linux version is stable for daily use, but edge cases exist around Wayland compositor compatibility, HiDPI scaling on multi-monitor setups, and input method support for non-Latin scripts. If you run a standard Linux desktop with X11 or a major Wayland compositor (GNOME, KDE, Sway, Hyprland), Zed works well. More niche compositors may have rendering quirks that are still being resolved.

No Remote SSH Development (Yet)

VS Code's Remote-SSH extension lets you edit files on a remote server with local editor performance. Zed does not have this capability yet. Remote development is on Zed's roadmap and is one of their most requested features. For now, if you need to edit files on remote servers, you can use Zed's terminal to SSH into the server and edit with Neovim or Helix, or use SSHFS/SFTP to mount remote directories locally.

No Windows Support

Zed does not support Windows as of early 2026. Windows support is in development but has no firm release date. If your team works across macOS, Linux, and Windows, this limits Zed to a subset of your developers. For Windows users who want similar performance characteristics, Neovim or the Helix editor are the closest alternatives.

Debugger Integration

Zed's debugger support through DAP (Debug Adapter Protocol) is functional but less polished than VS Code's mature debugging experience. Breakpoints, step-through, and variable inspection work for supported languages, but the UI for complex debugging scenarios (conditional breakpoints, watch expressions, multi-threaded debugging) is still evolving.

No Notebook Support

Jupyter notebook editing is not supported in Zed. ML engineers who rely on .ipynb files for exploratory data analysis will need to keep Jupyter Lab or VS Code available for notebook work. This is a significant gap for data science workflows specifically.

Frequently Asked Questions

Is Zed free?

Yes. Zed is open source under the GPL license. The editor, including all AI features that use your own API keys, is completely free. Zed offers optional paid services for cloud-based AI (using Zed's API quota instead of your own) and enhanced collaboration features, but these are not required to use the editor.

Can I use Zed with my existing VS Code extensions?

No. Zed uses its own WASM-based extension system, not the VS Code extension API. Extensions must be written specifically for Zed. However, because Zed supports LSP natively, most language intelligence features (autocomplete, diagnostics, formatting) work through the same language servers that VS Code extensions use. You lose VS Code-specific UI extensions but retain core development tool support.

Does Zed support Vim keybindings?

Yes. Zed includes a built-in Vim emulation mode that supports normal, insert, visual, visual-line, and command modes. It handles motions, text objects, registers, marks, and macros. Set "vim_mode": true in settings.json to enable it. The implementation is not a plugin; it is built into the editor core, which means Vim keybindings work in every context including the file finder, command palette, and terminal.

How does Zed compare to Cursor for AI coding?

Cursor forks VS Code and adds deep AI integration including tab completion, chat, and codebase-aware editing. Zed builds AI natively without forking another editor. The main differences: Cursor inherits VS Code's extension ecosystem (a major advantage), while Zed offers dramatically better performance and real-time collaboration. For AI features specifically, both support Claude and GPT-4, both support inline transforms, and both support project-context-aware chat. Choose Cursor if you need VS Code extensions. Choose Zed if performance and collaboration matter more. See our Cursor setup guide for a detailed comparison.

Can I use Zed for web development?

Yes. Zed has strong support for TypeScript, JavaScript, HTML, CSS, React, Vue, and Svelte through LSP and Tree-sitter. The built-in terminal runs dev servers, and the multi-buffer search handles project-wide refactoring. The main gap compared to VS Code is extension-based tooling: if you rely on specific VS Code extensions for your framework (like the Angular Language Service or the Svelte extension), check that Zed has equivalents before switching.

Does Zed work with Git?

Yes. Zed includes built-in Git integration: inline blame annotations, gutter indicators for modified/added/removed lines, a Git status panel, and diff views. It does not include a full Git GUI like VS Code's Source Control panel, so complex operations (interactive rebase, conflict resolution) are better handled in the terminal or a dedicated Git tool. For everyday commit, push, and blame workflows, Zed's built-in Git features are sufficient.

Is Zed suitable for large enterprise codebases?

Zed handles large projects well due to its Rust-based file indexing and GPU rendering. The 15,000-file monorepo in our benchmarks is representative of a mid-size enterprise project, and Zed performed strongly. The main enterprise concern is the lack of remote SSH development, which is critical for organizations where code lives on remote servers or cloud development environments. This feature is on Zed's roadmap. Once it ships, Zed becomes a viable enterprise editor.

Getting Started With Zed

Install Zed, open a project directory, and spend your first session configuring the AI assistant with your preferred provider. The AI features are what set Zed apart from being "just another fast editor," and experiencing inline transforms on real code is the fastest way to understand why this editor has momentum. If you are coming from VS Code, enable the VS Code keymap to preserve muscle memory while you explore Zed's unique features like multi-buffer editing and collaboration.

For organizations evaluating development tools for AI engineering, cybersecurity work, or compliance-sensitive environments, the combination of native performance, built-in AI, and real-time collaboration makes Zed worth a serious evaluation. If your team needs guidance on AI-powered development workflows, secure development environments, or integrating AI tools into your engineering stack, contact Petronella Technology Group at (919) 348-4912.

About the Author: Craig Petronella is the CEO of Petronella Technology Group, a cybersecurity and IT infrastructure firm in Raleigh, NC. With CMMC-RP, CCNA, CWNE, and DFE certifications and over 30 years in IT, Craig’s team builds AI-powered development and security infrastructure for businesses across the Southeast.