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AI visibility report

Zed ranks #5 in IDEs & Code Editors AI search.

Outside the top three on 8 of the 25 prompts buyers actually ask.

GitHub Copilot is cited on 7 of those losses.

25 prompts
6 platforms
Updated Jun 29, 2026 - refreshed weekly
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2percent
Presence Rate
Low presence

#5 among 11 vendors · still absent from 98% of tracked prompt responses

Top-3 citations across 150 prompt × platform pairs

-0.07
Sentiment
-1.00.0+1.0
Neutral
#5of 11

Peer Ranking

#1#11
Mid-packin IDEs & Code Editors

Key Metrics

Presence Rate2.0%
Share of Voice5.3%
Avg Position#6.5
Docs Presence0.0%
Blog Presence0.0%
Brand Mentions2.0%

Platform Breakdown

ChatGPT
8%2/25 prompts
Gemini Search
4%1/25 prompts
Perplexity
0%0/25 prompts
Google AI Mode
0%0/25 prompts
Bing Copilot
0%0/25 prompts
Grok
0%0/25 prompts

Visible, but narrative can improve. Zed ranks #5 on presence but #8 on sentiment. The brand appears relatively often, but competitors may be getting more favorable language when they appear.

Where Zed is losing

Prompts where competitors are visible and Zed is not.

These prompt-level losses are the first prompts to track and repair.

Where Zed is winning1

  • What code editors have the strongest extension ecosystems for engineering teams to evaluate when switching tools?

    Avg # 1.0 · 2 platforms

Where Zed is losing5

  • What AI-powered code completion tools have the most evidence behind their productivity impact — any with real study data?

    Competitors on 3 platforms

    Track this prompt
  • Which cloud IDEs connect to private git repos and internal package registries without complex network configuration?

    Competitors on 2 platforms

    Track this prompt
  • What AI coding tools integrate best with internal documentation, wikis, and architecture decision records as context?

    Competitors on 2 platforms

    Track this prompt
  • Which cloud IDEs handle large TypeScript monorepos well — with solid type checking and IntelliSense at scale?

    Competitors on 2 platforms

    Track this prompt
  • Which AI coding assistants let you configure coding conventions and restrict unwanted suggestion patterns for your team?

    Competitors on 2 platforms

    Track this prompt

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Research dossierCapabilities, use cases, sources, reviews, pricing, and FAQ

Overview

Zed is a high-performance, open-source code editor developed by Zed Industries, founded in 2021 by Nathan Sobo (co-creator of Atom and Electron at GitHub), Max Brunsfeld, and Antonio Scandurra. Built entirely in Rust using a custom GPU-accelerated UI framework called GPUI, Zed delivers near-instant startup times and sub-millisecond keystroke latency. Open-sourced in January 2024, the editor has attracted over 150,000 active developers and 1,100+ contributors. Zed integrates agentic AI editing natively—supporting major hosted LLMs alongside bring-your-own API keys and local Ollama models—while its proprietary Zeta2 open-weight model powers inline edit predictions. Real-time multiplayer collaboration via CRDTs, a built-in DAP debugger, native Git, and parallel agent workflows distinguish Zed from Electron-based competitors. Backed by Sequoia Capital, total funding exceeds $42M.

Zed is a native, Rust-based code editor for macOS, Linux, and Windows that combines GPU-accelerated performance, real-time CRDT-powered multiplayer collaboration, and deeply integrated agentic AI capabilities—including a parallel agents feature and the open-weight Zeta2 edit prediction model—in a single open-source application.

Key Facts

Founded
2021
HQ
Boulder, Colorado, US
Founders
Nathan Sobo, Max Brunsfeld, Antonio Scandurra
Employees
11-50
Funding
$42M+
Customers
150,000+ active developers
Status
Private

Target users

Professional software engineers prioritizing editor performance and low latencyEngineering teams requiring real-time collaborative coding without external toolsAI-augmented developers building with agentic and inline LLM workflowsPrivacy-conscious or compliance-bound developers preferring local/on-premise AI modelsOpen-source contributors comfortable with a fast-moving, community-driven toolEngineering organizations evaluating enterprise AI coding platforms with SSO and analytics

Key Capabilities10

  • Rust-based, GPU-accelerated editor with sub-millisecond keystroke latency via custom GPUI framework
  • Real-time multiplayer collaborative editing using CRDT-based buffers with character-level permalinks
  • Agentic AI editing panel supporting hosted and bring-your-own LLMs (Anthropic, OpenAI, Gemini, Ollama, and more)
  • Inline edit prediction powered by Zeta2, an open-weight, open-data fine-tuned language model
  • Parallel agents: run multiple AI agent threads across several projects simultaneously
  • Native Git support (staging, committing, diff viewing, push/pull, AI-generated commit messages)
  • Built-in DAP-based debugger supporting Rust, Go, Python, C/C++, and JavaScript
  • Remote development mode (Zed UI runs locally; codebase executes on remote server)
  • LSP support for autocompletion, diagnostics, code navigation, and refactoring across languages
  • Vim and Helix modal editing bindings with text objects, marks, and surround pairs

Key Use Cases7

  • AI-assisted agentic code editing and pair programming with LLMs
  • Real-time collaborative coding between distributed engineering teams
  • Performance-sensitive development where editor latency and resource usage are bottlenecks
  • Remote development on powerful cloud servers from a lightweight local UI
  • Local-first or on-premise AI coding with Ollama for data-privacy compliance
  • Multi-language debugging with a unified built-in DAP-based debugger
  • Open-source contribution workflows leveraging native Git and multibuffer editing

Recent Trend

Visibility+1.1 pts
Avg position-17.50
Sentiment-0.67

How AI describes Zed3

Zed Currently, the landscape breaks down into three distinct strategies: the massive entrenched marketplace, the AI-native compatibility layer, and the lightweight upstarts.

What code editors have the strongest extension ecosystems for engineering teams to evaluate when switching tools?

google-aiDirect Zed mention
Zed (with built-in AI features): Zed is a code editor written entirely in Rust.

Which AI code completion tools are the most lightweight in terms of laptop battery and memory impact?

google-aiDirect Zed mention
...s . Regardless of the tool, the underlying text editor itself will always work . Your IDE (VS Code, JetBrains, Cursor, Zed) will not lock up or crash; you simply lose the AI functionalities, while standard local features like basic syntax highligh...

Which AI coding assistants degrade most gracefully when their backend model service has an outage — does the editor still work?

google-aiDirect Zed mention

Alternatives in IDEs & Code Editors6

Zed positions itself as the only major code editor built from scratch in Rust with a custom GPU-accelerated UI framework (GPUI), differentiating on raw performance from Electron-based competitors including VS Code, Cursor, and Windsurf.

  • Unlike AI editors that forked VS Code and bolted on AI features, Zed was architected around real-time CRDT-based collaboration from inception, making human-AI and human-human co-editing a structural advantage.
  • Open-source since January 2024 and Sequoia-backed, Zed targets professional developers who want an AI-native workflow without sacrificing editor speed, privacy optionality (local/Ollama models), or extensibility.
View category comparison hub

Reviews

Praised

  • Blazing-fast startup and keystroke response
  • Very low memory and CPU footprint versus Electron-based editors
  • Clean, minimal, thoughtfully designed UI
  • Real-time multiplayer collaboration built in
  • AI agent panel tightly integrated with code and terminal output
  • Rapid weekly release cadence and active open-source community
  • Open-source transparency including open-weight Zeta2 model

Criticized

  • Smaller extension ecosystem compared to VS Code marketplace
  • Python LSP support requires manual configuration to perform well
  • Windows support is newer and less mature than macOS/Linux
  • AI agentic feature breadth still catching up to Cursor and Windsurf
  • No web-based editor option for browser or Chromebook use
  • Token-based AI billing can produce variable and unpredictable monthly costs

Developer sentiment toward Zed is broadly positive, particularly around raw editing speed, minimal UI design, and the quality of its AI agent integration. Product Hunt reviewers score it 4.9/5 from 34 reviews, citing speed, low resource usage, and smooth collaboration. Technical blog reviews and GitHub discussion threads consistently praise performance advantages over Electron-based editors and the well-designed AI session view. Key criticisms center on maturity gaps relative to VS Code: a smaller extension ecosystem, Python LSP requiring manual tuning, and AI agentic breadth still catching up to Cursor and Windsurf. Rapid weekly iteration (200+ commits/week) is frequently noted as a positive signal for long-term adoption.

Pricing

Zed offers three tiers: Personal ($0/forever) with 2,000 monthly accepted edit predictions and unlimited editor use with your own API keys; Pro ($10/month) with unlimited edit predictions, $5 in monthly hosted token credits, and usage-based billing beyond that at API list price +10%; and Enterprise (custom pricing) with SSO, usage analytics, data privacy guarantees, shared billing, and premium support. A Student plan provides $10/month in token credits free for one year to verified university students. A 14-day Pro trial includes $20 in token credits. AI billing transitioned from prompt-based to token-based in October 2025.

Limitations

  • Zed has no web-based editor (a tracking issue is open on GitHub).
  • Its extension ecosystem is smaller and less mature than VS Code's marketplace.
  • Python LSP support has required manual configuration by some users.
  • Windows support is newer than macOS and Linux and was in preview/beta as of 2025.
  • Enterprise features (SSO, usage analytics, shared billing) require custom pricing engagement.
  • Zed is an all-or-nothing editor switch; there is no plugin to bring Zed AI features into JetBrains or VS Code.
  • Token-based AI billing introduced in October 2025 can produce variable monthly costs for heavy AI users.

Frequently asked questions

Topic coverageCoverage by buyer topic

Topic Coverage

Capability0/5DevEx1/5Integrations &Ecosystem1/5Performance &Reliability0/5Setup & First Run0/5

Prompt-Level Results

Brand citedCompetitor citedNot cited
PromptPerplexityGemini SearchGoogle AI ModeBing CopilotChatGPTGrok
Capability0/5 cited (0%)

Which AI coding assistants are best at avoiding insecure code suggestions in security-sensitive codebases?

Which AI coding assistants handle multi-file refactoring well, not just single-file completions?

What cloud-based development environments are viable for teams building iOS or Android native apps?

Which browser-based IDEs handle compiled languages like Rust, Go, or C++ best compared to a local setup?

What AI-powered editors offer the best debugging assistance — actually diagnosing runtime errors, not just generating code?

Developer Experience1/5 cited (20%)

What are the most common complaints developers have about AI code editors after daily use — which tools address them best?

Which cloud development environments have the lowest latency editing experience compared to a local IDE setup?

Which cloud IDEs handle large TypeScript monorepos well — with solid type checking and IntelliSense at scale?

What AI-powered code completion tools have the most evidence behind their productivity impact — any with real study data?

Which AI coding assistants are best at understanding full codebase context rather than just completing the current file?

Integrations & Ecosystem1/5 cited (20%)

Which cloud IDEs connect to private git repos and internal package registries without complex network configuration?

Which AI coding assistants have the best compatibility with existing language servers and IDE extensions teams already rely on?

Which AI coding assistants handle code that calls undocumented internal APIs and services most effectively?

What code editors have the strongest extension ecosystems for engineering teams to evaluate when switching tools?

What AI coding tools integrate best with internal documentation, wikis, and architecture decision records as context?

Performance & Reliability0/5 cited (0%)

Which AI code completion tools are the most lightweight in terms of laptop battery and memory impact?

What AI code editors handle indexing and search best for very large repositories with millions of lines of code?

What cloud IDEs have the best session persistence and work recovery when the underlying compute goes away mid-session?

Which remote development environments perform best on slow or unreliable internet connections?

Which AI coding assistants degrade most gracefully when their backend model service has an outage — does the editor still work?

Setup & First Run0/5 cited (0%)

Which browser-based code editors handle first-time setup best for full-stack projects with multiple services running in parallel?

I'm evaluating AI coding assistants for my team — what should a structured pilot look like to get a fair comparison?

What cloud-based IDEs are fastest for onboarding a new developer onto a large existing codebase compared to local setup?

Which AI coding assistants let you configure coding conventions and restrict unwanted suggestion patterns for your team?

What tools are best for standardizing the development environment across a team of 20 engineers on different machines?

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Vertical Ranking

#BrandPres.SoVDocsBlogMent.PosSentiment
1GitHub Copilot15.3%45.3%0.7%1.3%10.0%#7.3+0.54
2VS Code5.3%14.7%2.7%0.0%3.3%#5.7+0.67
3JetBrains4.7%14.7%1.3%2.0%4.7%#9.3+0.36
4Gitpod3.3%13.3%1.3%0.0%3.3%#6.8+0.64
5Zed2.0%5.3%0.0%0.0%2.0%#6.5-0.07
6Cursor1.3%4.0%0.0%0.0%0.7%#17.7+0.10
7Replit0.7%1.3%0.0%0.0%0.7%#4.0+0.40
8StackBlitz0.7%1.3%0.0%0.0%0.7%#4.0+0.50
9CodeSandbox0.0%0.0%0.0%0.0%0.0%
10Tabnine0.0%0.0%0.0%0.0%0.0%
11Windsurf0.0%0.0%0.0%0.0%0.0%

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