Tabby

Overview

Tabby is the leading open-source alternative to GitHub Copilot for organizations that need their code to stay on their own hardware. Built by TabbyML, the project has grown to over 32,000 GitHub stars by offering a Copilot-grade autocomplete and chat experience that runs entirely on customer-controlled infrastructure - whether that is a beefy workstation, a self-hosted GPU server, or a private cloud cluster.

The project recently expanded beyond completions with an agent called Pochi, which adds full-stack task planning and execution similar to Cursor's Composer mode. The combination of self-hosted privacy and modern agentic capabilities makes Tabby a credible choice for enterprises that previously had to choose between security and capability.

Core Features

Tabby's core is its completion engine. The Tab model produces context-aware code suggestions in milliseconds, drawing on Tabby's project indexing to understand your codebase. The Answer Engine provides instant coding answers without leaving your IDE, and the Inline Chat lets you ask questions or request edits in context.

Data Connectors let Tabby pull from internal documentation, Confluence pages, Jira tickets, or other knowledge sources so completions and chat answers can reference your actual project context, not just open files.

The Pochi agent is the newest addition. It handles multi-step tasks like writing entire features, refactoring across files, and managing test cycles, similar to the Composer and Agent modes in commercial editors. Pochi can run as a cloud service or alongside a self-hosted Tabby deployment.

IDE support is exceptionally broad. Tabby has official plugins for VS Code, Neovim, IntelliJ, Eclipse, Android Studio, AppCode, CLion, GoLand, PhpStorm, PyCharm, Rider, RubyMine, and WebStorm. Few competitors match this breadth.

Model support includes open weights from Mistral, DeepSeek, Qwen, and StarCoder. Customers can also point Tabby at their own self-hosted model.

Pricing Analysis

The Community plan is free for individuals and small teams up to a handful of seats. It includes the core completion engine and basic chat. Paid Team and Enterprise plans add user management, audit logs, SSO, advanced data connectors, and priority support. TabbyML does not publish exact prices for Team or Enterprise tiers publicly - the company quotes per-seat pricing based on deployment size, typically in the $10 to $30 per seat per month range based on customer reports.

Because Tabby runs on your hardware, the real cost beyond seats is the GPU - a consumer-grade GPU can serve a small team, while larger deployments need dedicated A10 or L4 cards.

Who Should Use Tabby

Tabby is the strongest choice for security-conscious teams that need a Copilot replacement with no code leaving the organization. Defense contractors, regulated financial firms, healthcare companies, and government users get the most value. Indie developers who run their own hardware and want a free Copilot alternative are also a fit through the Community plan.

It is less suited for teams that prefer a fully managed SaaS experience or want bleeding-edge model quality - the self-hosted models, while strong, generally trail frontier commercial models on the hardest tasks.