Zed vs Poolside

Detailed side-by-side comparison to help you choose the right tool

Zed

🔴Developer

AI Coding Assistants

High-performance, multiplayer code editor from the creators of Atom and Tree-sitter, with native AI agents and MCP support.

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Starting Price

Custom

🔴Developer

AI Coding Assistants

Foundation-model company building enterprise-grade AI software engineers trained on private code with on-prem deployment.

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Starting Price

Custom

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Feature	Zed	Poolside
Category	AI Coding Assistants	AI Coding Assistants
Pricing Plans	420 tiers	83 tiers
Starting Price
Key Features	• GPU-Accelerated Rendering: Uses Metal on macOS and Vulkan on Linux to render the entire UI on the GPU, achieving sub-millisecond keystroke latency and smooth scrolling even in very large files with thousands of lines of code. • Built-in AI Assistant: Integrated assistant panel supporting Claude, GPT-4, Gemini, and other LLMs for code generation, refactoring, explanation, and inline transformations with full project-wide context indexing for deeper codebase understanding. • Real-Time Multiplayer Collaboration: CRDT-based collaboration engine allows multiple developers to edit the same workspace simultaneously with live cursors, shared terminals, and zero-conflict merging.	• Software-engineering focused foundation-model company rather than a lightweight autocomplete plug-in • Enterprise positioning for private, secure, and regulated development workflows • Targets teams that need coding assistance with stronger control over data, deployment, and governance

✓Rust-native, GPU-accelerated interface is designed for low-latency editing
✓Real-time collaboration is built into the editor instead of added by an extension
✓Agent panel, multiple model providers, and MCP support consolidate common AI workflows

✗A smaller extension ecosystem can block teams dependent on VS Code-specific tooling
✗Hosted AI prices and usage allowances require current vendor verification
✗MCP-connected tools introduce credential and approval risks that need explicit controls

✓Best-in-class data residency story — model can run fully inside your VPC or air-gapped environment
✓Custom training on private code produces depth no public copilot can match
✓Founding team (ex-GitHub) has credibility with enterprise procurement and security teams
✓Includes evals and observability so you can prove ROI to a CIO, not just guess

✗Enterprise-only — no self-serve tier and no way to try it without a long sales cycle
✗You take on a heavy GPU footprint and the operational burden of running foundation models in-house
✗Product surface and exact naming are still shifting — flagged for manual verification
✗For most companies, GitHub Copilot Enterprise or Cursor delivers 90% of the value at a fraction of the cost

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