AI / LLM · PRO TIER

TabbyMLpro

Tabby is a self-hosted AI coding assistant — a Copilot alternative that runs on your infrastructure. Code completion, chat-with-codebase, repository context, all via local LLM. Native IDE plugins for VS Code, JetBrains, Vim, Emacs. Designed for teams where proprietary code can't leave the network.

Install via WHMCS → Visit tabbyml.com ↗

🤖 AI / LLM Min 6144 MB RAM Port 8080 (http) Tier pro

// What it is

A closer look.

It's the answer to "I want Copilot but my legal department won't let me ship our codebase to GitHub".

// Use cases

What it's for.

Concrete scenarios where teams pick TabbyML over the SaaS alternative.

◆

Code completion

Copilot-style inline suggestions on your code

◈

Chat with codebase

ask questions about your repo via natural language

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Code review assist

AI review on pull requests before human review

▣

Refactoring helper

bulk transformations across files with AI

▦

Privacy-bound development

proprietary code stays in-network

// Who it's for

Built for these teams.

If your team profile matches one of these, TabbyML is a strong fit out of the box.

Profile A

Enterprises with code privacy policies

rejecting GitHub Copilot for compliance

Profile B

Defense / government dev teams

under no-cloud-code mandates

Profile C

Financial services

working on proprietary trading algos

Profile D

Open-source organizations

wanting self-hosted dev tooling

Profile E

Indie developers

preferring self-hosted to per-seat SaaS billing

// Differentiators

Why teams pick TabbyML.

When evaluating self-hosted options for this category, here are the dimensions on which TabbyML consistently lands above the alternatives.

✓Self-hosted Copilot — full feature parity with GitHub Copilot UX
✓Apache 2.0 — commercial use unrestricted
✓Code privacy — your code never leaves your network
✓Multiple IDE support — VS Code, JetBrains, Vim, Emacs
✓Repository context — RAG over your codebase, not just current file
✓Team management — multi-user with usage tracking

// Integrations

Connects to.

The stack you'll plug TabbyML into — services, protocols, and adjacent apps in the BluixApps catalog.

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IDE plugins

VS Code, JetBrains (IntelliJ, PyCharm, GoLand), Vim, Emacs

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LLM backends

Tabby ships with optimized code models; supports custom OpenAI-compatible

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Repository sources

Git, GitLab, GitHub, Gitea, Bitbucket

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Authentication

built-in users + LDAP / OAuth via reverse proxy

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Code search

semantic search over indexed repositories

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Webhook

code review automation on PR events

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API

REST endpoints for programmatic access

// Adoption & deployment

Notable users & community

23k+ GitHub stars
Active Slack community
Featured in self-hosted dev tools guides
Backed by TabbyML with sustainable commercial enterprise offering
Continuous model improvements tracking SOTA code LLMs

What we ship

Docker compose: Tabby server + persistent index volume
Pinned tabbyml/tabby:latest (release-tagged)
HTTPS via Let's Encrypt
Default model: StarCoder2 for code completion
GPU passthrough optional (highly recommended for production)
Admin user with random password on first boot
Backup hook covers index + user data

// Tips & operations

Run it properly.

Operational guidance from running this in production — what to do before you scale, what to lock down, what surprises people.

// PERFORMANCE

GPU strongly recommended

code completion latency on CPU is too high for usable IDE experience

// SECURITY

Repository indexing is slow

first index of large monorepos takes hours; let it run

// OPERATIONS

Update model frequently

code LLMs evolve fast; quarterly model swaps improve completion quality

// RELIABILITY

Set up SSO

multi-user setup needs OAuth / LDAP from day one; avoid local user proliferation

// DEPLOYMENT

Watch token costs if using OpenAI

code completion = high token volume; local model preferred

// SCALING

Persistent volume

indexed repos + chat history live on disk; mount from day one

6144

// min ram (MB)

// min disk (GB)

8080

// access port

http

// protocol

pro

// bluixapps tier

8080:8080

// docker image

Project resources

Official sitetabbyml.com ↗

// Alternatives in AI / LLM

Compare with