Tabby is an open-source, self-hosted AI coding assistant built by TabbyML — a private alternative to GitHub Copilot, Cursor, and Tabnine that runs entirely on hardware you control. We rate it 86/100: it is the most complete self-hosted Copilot replacement we have tested in 2026, and the right pick for security-conscious teams that cannot ship code to a third-party AI service.

What is Tabby?

Tabby is a self-contained AI coding platform that bundles three things into a single binary: a code-completion engine, an in-IDE chat ("Inline Chat"), and an Answer Engine that retrieves context from your own repos, docs, and issues. It is built by TabbyML, Inc., the YC-backed startup that raised a $3.2M seed in October 2023. The first commit landed on March 16, 2023, and the project debuted on Hacker News in April 2023 with a 627-point Show HN. The repo at TabbyML/tabby currently sits at 33,477 stars and 1,743 forks, and the latest stable release is v0.32.0, shipped on January 25, 2026.

What separates Tabby from generic inference servers like Ollama or vLLM is that it is purpose-built as a Copilot replacement. You get an admin dashboard, team management, IDE plugins for VS Code, JetBrains, and Vim, OAuth/SAML SSO, a code-context indexer that ingests your private GitHub or GitLab repos, and a built-in RAG pipeline — all in one Docker container. No external database, no cloud account, no telemetry leaving your network.

Tabby code completion suggesting a SQL CREATE TABLE migration inside an IDE — Tabby's code-completion engine suggesting a SQL migration inline in the editor — the model runs locally on your own GPU.

Key Features of Tabby

Three products in one binary: Code Completion, Inline Chat, and Answer Engine all ship in a single Docker container — docker run -p 8080:8080 tabbyml/tabby and you have the full stack running.
Bring-your-own model: Native support for DeepSeek-Coder, Qwen 2.5 Coder, StarCoder2, CodeLlama, and Mistral — plus any OpenAI-compatible endpoint, so you can mix local models with frontier APIs.
Codebase-aware RAG: Tabby indexes your private Git repos and uses rank fusion to feed the most relevant snippets into completions and chat — the feature that makes it actually useful on large codebases.
Consumer-GPU friendly: A 7B model in int8 mode runs on roughly 8 GB of VRAM — so a single RTX 3090, 4070, or even an Apple M1/M2 with Metal can serve a small team.
Real IDE plugins, not a wrapper: First-party extensions for VS Code, JetBrains, Vim/Neovim, and Sublime Text — not a glorified curl wrapper.
Enterprise plumbing built-in: Admin dashboard, OAuth (GitHub, Google, GitLab), SAML SSO, audit logs, rate limiting, and team-based access control.
Data Connectors: Pull context from GitHub, GitLab, Confluence, Google Docs, and your own websites — the Answer Engine cites sources just like Perplexity does.

Tabby Answer Engine showing cited sources from a private GitHub repository — Tabby's Answer Engine retrieves and cites context from your own repos, docs, and commits — not a public web index.

What Users Say About Tabby

Sentiment is mostly positive among self-hosters but realistic about trade-offs. The 627-point Show HN thread on Hacker News in April 2023 praised the project for being a "real" self-hosted Copilot rather than a research demo, and the follow-up 366-point thread in January 2025 noted a clear quality jump after Tabby added its Answer Engine. On r/selfhosted and r/LocalLLaMA, top-voted posts call Tabby "the only self-hosted Copilot that actually works on a real codebase," and admins point to the dashboard and SSO as why it survived a security review when generic Ollama setups didn't.

The recurring complaints are honest. Out-of-the-box completion quality with a 1B or 7B local model is noticeably below GitHub Copilot — reviewers at Sider and ML Journey both call this out. You need either a larger model (and the GPU to match) or to wire Tabby up to an OpenAI-compatible endpoint to close the gap. The project also moves fast: minor versions occasionally break Docker image tags, and the v0.32 release notes still list "v0.x" — there is no 1.0 yet, which is a fair concern for risk-averse buyers. Finally, the GitHub license is technically "Other" (a custom Apache-2-with-noncommercial-clauses for some hosted features), which trips up some compliance teams.

Tabby Pricing

Tabby is dual-licensed: the source code is open and free to self-host, with paid plans for managed deployments and enterprise features.

Plan	Price	Best For
Community	Free / Open Source	Up to 5 users, local deployment, code completion + chat + Answer Engine + Context Provider.
Team	$19 / user / month	Up to 50 users, flexible deployment, growing engineering teams.
Enterprise	Custom (contact sales)	Unlimited users, customized deployment, enhanced security, group management.

Hardware cost is on you for self-hosting: budget roughly $1,500–$2,500 for an RTX 3090 or 4090 if you want a serious 7B–13B model serving 5–10 developers comfortably.

Who Should Use Tabby?

Best for: Engineering teams at security-conscious companies (finance, healthcare, defense, government) where shipping source code to a third-party AI is a non-starter. Also: small teams with existing GPU hardware who don't want per-seat Copilot bills, and tinkerers who actually enjoy running their own AI stack.

Not ideal for: Solo developers who just want the best completions out of the box — Cursor or Copilot will be faster, smarter, and cheaper than buying a GPU. Also a poor fit for teams without anyone willing to own GPU drivers, Docker, and model-management problems.

Pros and Cons

Pros:

Genuinely self-contained — one Docker command and you're running, no required cloud accounts.
The Answer Engine with private-repo RAG is the killer feature; nothing else in the open-source space matches it.
Real, maintained IDE plugins for VS Code, JetBrains, Vim, and Sublime — first-party, not community wrappers.
Free for up to 5 users with no functional crippling, which is rare among "open core" tools.
Active development — 33k+ stars, weekly commits, and a real company behind it after the YC-backed seed round.

Cons:

Default local-model quality lags GitHub Copilot until you wire up a larger model or an OpenAI-compatible endpoint.
No 1.0 yet; minor versions occasionally break Docker tags or migrations.
Custom license ("Other") means compliance teams have to read the fine print — it is not a clean MIT or Apache-2 grant.
Realistic GPU requirement: 8 GB VRAM minimum for int8 7B, more like 24 GB for anything competitive on a team.

Alternatives to Tabby

The closest alternatives are Continue, an open-source IDE extension that brings your own model (we reviewed Continue), and Cody by Sourcegraph, which has stronger codebase search but is not as cleanly self-hostable. GitHub Copilot ($10–$19/seat) wins on raw completion quality but ships your code to Microsoft. For the no-IDE crowd, Aider is the terminal-native option that pairs nicely with local models via Ollama.

Verdict: Is Tabby Worth It?

If your company will not let you use Copilot or Cursor — or you are an OSS purist who refuses on principle — Tabby is the best self-hosted answer in 2026. Pair it with DeepSeek-Coder or Qwen 2.5 Coder on a single 24 GB GPU, point it at your private GitHub org, and a five-person team gets a Copilot-shaped experience for the price of one used 3090. We rate it 86/100: not the best AI coding assistant, but the best one you can run entirely on your own metal.

Frequently Asked Questions

Is Tabby free?: Yes. The Community edition is free and open source for up to 5 users with full features (code completion, Inline Chat, Answer Engine, Context Provider). Paid Team plans start at $19/user/month for up to 50 users.
What hardware do I need to run Tabby?: Roughly 8 GB of VRAM is enough to run a 7B code model in int8 mode — an RTX 3060 12 GB, 3090, 4070, or Apple M1/M2 with Metal works. For 13B+ models or larger teams, an RTX 4090 or A100 is recommended.
How does Tabby compare to GitHub Copilot?: Copilot has better out-of-the-box completion quality and lower per-developer cost if you only have a few seats. Tabby wins on privacy (your code never leaves your network), customizability (any open-weights or OpenAI-compatible model), and total cost at scale.
Is Tabby open source?: Yes — the source is on GitHub, but under a custom "Other" license rather than MIT or Apache-2. Most self-hosting use cases are clearly permitted; check the LICENSE file before commercial redistribution.
What IDEs does Tabby support?: Tabby has first-party plugins for VS Code, JetBrains IDEs (IntelliJ, PyCharm, GoLand, etc.), Vim/Neovim, and Sublime Text. There is also a CLI for use with Helix and other editors via LSP.

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