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Home/Categories/AI & Machine Learning/Tabby
Icon for Tabby

Tabby

Open source alternative to GitHub Copilot, JetBrains AI Assistant and Tabnine

  • 33.9K stars
  • Apache-2.0
  • Updated this year
  • Last commit 113 days ago

Last verified Sep 30, 2026

Run a private AI coding assistant server with Tabby to deliver code chat and completion inside your network, with self-hosted control for regulated teams.

Visit websiteGitHub33.9K starsDeploy on Hostinger
image of Tabby
TL;DR

Tabby is a self-hosted AI coding assistant for code completion, chat, and on-premises developer assistance. It replaces GitHub Copilot for teams that want model and code privacy, OpenAPI integration, and support for consumer-grade GPUs.

Read the full breakdownHide the full breakdownWho it is for, how it works, trade-offs and the FAQ
who it's for

Who Tabby is for#

Engineering teams with private code

Use Tabby to provide AI coding help without sending code context to a hosted copilot provider.

Skip if:

Skip if your company is comfortable with GitHub Copilot and wants no inference operations.

Platform teams standardizing internal AI dev tools

Use the OpenAPI interface to connect code assistance into internal IDE or cloud development environments.

Skip if:

Skip if each developer uses unrelated editors and no one can operate shared infrastructure.

the problem

The problem it solves#

AI coding tools can expose code context to vendor infrastructure and create procurement friction for teams with private repositories. Hosted copilots also give teams limited control over models, inference infrastructure, and data boundaries.

how Tabby solves it

How it solves it#

Self-contained coding assistant

The README describes Tabby as self-contained with no DBMS or cloud service required, lowering deployment dependencies.

OpenAPI interface

Tabby exposes an OpenAPI interface, making it easier to integrate with existing developer infrastructure and cloud IDEs.

Consumer GPU support

The README states Tabby supports consumer-grade GPUs, which helps small teams experiment without enterprise inference hardware.

strengths · trade-offs

Strengths and trade-offs#

Strengths

  • Private code assistanceSelf-hosting keeps repository context and prompts inside infrastructure the team controls, which matters for proprietary codebases.
  • Copilot-like workflow without vendor lock-inTabby targets code assistance while giving operators control over deployment and model choices.

Trade-offs

  • -Inference quality depends on models and hardwareHosted tools may provide stronger default models and less setup. Tabby requires operating the service and choosing hardware that matches developer expectations.
versus alternatives

Tabby vs alternatives#

Tabby vs GitHub Copilot

Tabby is better when code privacy, self-hosting, and model control matter more than a managed copilot experience. GitHub Copilot is still easier for teams that want high-quality hosted models, broad editor support, and minimal infrastructure work.

tech stack · detected from GitHub

What it's built on#

Languages
PythonRust
Frameworks
React
frequently asked

FAQ#

What is Tabby?

Tabby is a self-hosted AI coding assistant and on-premises alternative to GitHub Copilot.

Does Tabby need a cloud service?

The README says Tabby is self-contained with no DBMS or cloud service required.

Can Tabby run on consumer GPUs?

Yes. The README says Tabby supports consumer-grade GPUs.

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Hostinger

Run Tabby on your own server

Self-host Tabby on a Hostinger VPS.

Deploy on Hostinger

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