Tabby
Self-hosted, open-source AI coding assistant with code completion, answer engine, inline chat, and the Pochi agent.
Pick Tabby when source code cannot leave your infrastructure and you have someone who can run model serving — you get a readable, modifiable assistant plus an autonomous agent that most self-hosted rivals don't ship. Skip it if you want zero-ops setup or need a free tier beyond five users; Team at $19/user/mo is the first plan that scales to 50. The open-source code is the real differentiator, not the feature checklist.
Verified 5d ago · liveness 72/100 · cite: rightaichoice.com/tools/tabby
- Teams that legally cannot send source code to a third-party cloud
- Enterprises with data sovereignty or supply-chain transparency requirements
- Engineering orgs with spare GPUs and someone to run local model serving
- Developers who want to read and modify their coding assistant's source
- Solo devs who want instant setup with no infrastructure to own
- Groups larger than 5 users expecting the free Community plan to cover them
- Teams that want a fully managed SaaS with no self-hosting involved
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Skip Tabby if you have no one to own GPU capacity and model-serving upgrades, or if your team is under 5 people and you want zero-setup autocomplete — the free Community tier caps at 5 users and local deployment.
Tabby Cloud bills on the token cost of the LLMs you run, so heavy Pochi usage on top of the $20 free monthly credits becomes a variable line item that's hard to forecast.
Community at $0/mo suits individuals and teams of up to 5 running Tabby locally. Team at $19/user/mo is the realistic floor for a company that needs SSO, usage reports, and up to 50 seats, and it undercuts most proprietary per-seat assistants that carry no self-hosting option. Enterprise is custom-priced for unlimited users. Tabby Cloud is pay-as-you-go with $20 in free monthly credits, best for small teams that want Tabby's features without running GPUs.
In short
Tabby — Self-hosted, open-source AI coding assistant with code completion, answer engine, inline chat, and the Pochi agent. Best for Teams that legally cannot send source code to a third-party cloud, Enterprises with data sovereignty or supply-chain transparency requirements, Engineering orgs with spare GPUs and someone to run local model serving. Free to start; paid plans from $19/user/mo.
What's new in Tabby
Checked 5 days agoAcross the latest 1 update: 1 feature update.
What people actually say about Tabby — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
39 mentions across 3 sources (Hacker News, Product Hunt, Lemmy) · researched Jul 3, 2026.
Average across the 3 sources that answered — each source counts once, not each post.
- +Fully self-hosted — code and data never leave your infrastructure.
- +Open-source with transparent and auditable codebase.
- +Supports consumer-grade GPUs — no expensive hardware required.
- +No external database or cloud services needed to run.
- +Works with popular IDEs and Neovim for integration.
- −Very limited community feedback — hard to validate real-world performance.
- −No major benchmarks comparing completion accuracy to competitors.
- −Lacks advanced features like multi-line or function-level completions?
- −Unknown support responsiveness and update frequency.
- −Self-hosting requires technical know-how to deploy properly.
- • Self-hosting requires hardware (GPU) and maintenance effort
- • Potential costs for GPU cloud instances if not running on-prem
Viability Score
How well maintained and how widely used is Tabby? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Real-time AI code completion with project context awareness
- Answer Engine that explains code and answers questions in the IDE
- Inline chat tied to the code you're editing
- Pochi agent that plans, executes, and checks in on tasks (July 18, 2025)
- Context Providers pull in docs, config files, and external APIs
- Doc Ingestion API for connecting your own documentation (May 2025)
- Self-hosted deployment including on consumer-grade GPUs
- No external DBMS or cloud service required
- Code Browser for browsing repository context
- Cloud IDE deployment support
- VS Code extension
- Neovim extension
- IntelliJ, Eclipse, Android Studio, and wider JetBrains IDE support
- Single Sign-On (SSO) on Team and Enterprise tiers
- Usage Reports and Analytics on Team tier
About Tabby
Tabby is an open-source AI coding assistant you run on your own infrastructure, including consumer-grade GPUs, with no external DBMS or cloud service required. It covers the everyday coding loop inside your IDE: real-time code completion that reads surrounding context, an Answer Engine that resolves coding questions without leaving the editor, and inline chat that stays tied to the file you're working in. Data Connectors (Context Providers) pull in documentation, config files, and external APIs so suggestions reflect your project's actual context, and a Doc Ingestion API shipped in May 2025 lets teams feed private documentation straight into Tabby. The Pochi agent, launched July 18, 2025, extends it beyond autocomplete into planning and executing multi-step tasks. Editor coverage spans VS Code, Neovim, IntelliJ, Eclipse, Android Studio, and the wider JetBrains family, with deployment left to you locally or via Tabby Cloud. Community is $0 for up to 5 users; Team runs $19/user/mo for up to 50 users, with Enterprise custom-priced. Tabby Cloud bills usage-based on LLM token cost with $20 in free monthly credits, and Tab Completion stays free.
Behind the Verdict
We'd reach for Tabby the moment a contract, regulator, or security review says source code stays on your iron. Nothing else in this category lets you read and modify the assistant itself, and that matters when your legal team asks who sees the code. The three pillars — code completion, Answer Engine, inline chat — cover the daily loop, and Data Connectors plus the May 2025 Doc Ingestion API are what make answers reference your repos rather than a generic public corpus. Pochi (July 18, 2025) is the part that changes the calculus: instead of suggesting the next line, it plans a task, executes it, and checks in through your existing tools. In practice that is where self-hosted setups usually fall behind cloud rivals, so it's worth testing early. Where it bites is operations. You own model serving, upgrades, and the GPUs; a consumer-grade card may be enough, but someone has to babysit it. The Community plan's five-user ceiling also arrives fast — once you pass it, Team at $19/user/mo is the tier that unlocks SSO, usage reports, and telemetry policy enforcement. Against GitHub Copilot or Codeium, Tabby trades polish for control; against other self-hosted options, it trades a smaller ecosystem for transparency and an agent you can actually inspect. If you just want autocomplete working in ten minutes, pass.
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Real-world workflow fit
Concrete scenarios for the personas Tabby actually fits — and what changes day-one when you adopt it.
Stand up Tabby on internal GPU hardware, point the Doc Ingestion API at the team's internal style guides, and roll out the VS Code and JetBrains extensions to a 40-person org under the Team plan.
Outcome: Developers get completion, answer engine, and inline chat without any source code leaving the company network, and SSO plus usage reports satisfy the security review.
Install the VS Code extension under the free Community plan, connect Context Providers to the repo's config files, and use the answer engine to explain unfamiliar modules.
Outcome: Coding questions get answered inside the editor instead of in a browser tab, at $0/mo for up to 5 users.
Assign Pochi a multi-step task — plan the change, execute it, check in with progress — inside the team's existing tools and workflows.
Outcome: The team hands off routine multi-step work rather than only accepting single-line completions, which is the capability most self-hosted assistants lack.
Use Cases
- Deploy a private AI coding assistant on your own server so source code never leaves your infrastructure.
- Accelerate coding with real-time completion that adapts to your codebase's context.
- Get instant coding answers inside the IDE without breaking flow to search externally.
- Connect internal docs or codebases via Context Providers for more relevant suggestions.
- Upload proprietary documentation through the Doc Ingestion API so answers cite your own material.
- Use Pochi to plan and execute multi-step coding tasks autonomously inside your existing tools.
- Run the assistant on consumer-grade GPUs without standing up an external DBMS or cloud service.
Models Under the Hood
as of 2026-10-17
Limitations
- Community is free but capped at 5 users with local deployment only.
- Team raises the cap to 50 users at $19/user/mo and adds SSO plus usage and telemetry reporting; Enterprise is custom-priced with unlimited users.
- Self-hosting requires your own infrastructure and compatible GPU hardware, including consumer-grade GPUs, plus someone to maintain model serving and upgrades.
- Tabby Cloud (Pochi) bills based on the token cost of the LLMs you run, with $20 in free monthly credits.
as of 2026-10-03
Verification history
We have re-verified Tabby 9 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 9 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Tabby tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Community
$0/mo
Ideal for
Individuals, freelancers, and small teams of up to 5 who will run Tabby on their own local or on-prem infrastructure.
What this tier adds
Free entry point: up to 5 users, local deployment, code completion, answer engine, inline chat, and Context Providers.
Team
$19/user/mo
Ideal for
Growing engineering teams of 6 to 50 that need SSO, usage reporting, and the ability to enforce an IDE/extensions telemetry policy.
What this tier adds
Raises the cap to 50 users, adds flexible deployment, Single Sign-On, usage reports and analytics, and a configurable telemetry policy, at $19/user/mo.
Enterprise
Custom
Ideal for
Large enterprises with unlimited seats, custom deployment requirements, and a need for group-level security management.
What this tier adds
Unlimited users, customised deployment, enhanced security and group management, a dedicated Slack channel, and roadmap prioritization; custom-priced.
Tabby Cloud (Usage-Based)
Pay-as-you-go
Ideal for
Small teams that want Tabby's features and Pochi without running their own GPUs, and are comfortable with variable token-based billing.
What this tier adds
Pay-as-you-go instead of a seat licence: $20 in free monthly credits, Pochi billed on LLM token cost, Tab Completion always free with no usage limits, and a user-set budget cap.
Where the pricing makes sense
The company stage and team size where Tabby's pricing actually pencils out — and where peers do it cheaper.
Community at $0/mo suits individuals and teams of up to 5 running Tabby locally. Team at $19/user/mo is the realistic floor for a company that needs SSO, usage reports, and up to 50 seats, and it undercuts most proprietary per-seat assistants that carry no self-hosting option. Enterprise is custom-priced for unlimited users. Tabby Cloud is pay-as-you-go with $20 in free monthly credits, best for small teams that want Tabby's features without running GPUs.
Setup time & first value
How long it actually takes to get something useful out of Tabby — broken out by persona, not the marketing-page minute.
Community/local: expect an afternoon to a few days, since you provide the infrastructure and run model serving yourself, then a few minutes per developer to install the VS Code, Neovim, or JetBrains extension. Team: same self-hosting work plus SSO and telemetry-policy configuration, so budget time with your identity provider. Tabby Cloud: fastest path — sign up, install the extension, and start
Switching to or from Tabby
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From GitHub Copilot: install the Tabby extension alongside Copilot, validate completion quality on your repo, then drop the Copilot subscription once the team is comfortable.
- →From Codeium: point the same IDE extensions at your self-hosted Tabby instance and re-create any context sources as Context Providers.
- →From an internal prompt-and-paste workflow: add Context Providers and the Doc Ingestion API so answers cite internal docs instead of pasted snippets.
- →From cloud IDE setups: Tabby supports Cloud IDE deployment, so existing browser-based workflows can be pointed at your instance.
- ↗To GitHub Copilot: remove the Tabby extensions and re-enable Copilot's native completions; you lose self-hosting and source-code sovereignty.
- ↗To Codeium: swap extensions and accept a cloud-hosted service in place of your own inference.
- ↗To a fully managed SaaS assistant: hand off model serving, GPU capacity, and upgrade work to the vendor, giving up the ability to read and modify the assistant's source.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Tabby”, and we withheld 6: 6 could not be judged, because “Tabby” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Tabby.
Official links
Tools that pair well with Tabby
Common stack mates teams adopt alongside Tabby, with the specific reason each pairing earns its keep.
Sourcegraph Cody
Sourcegraph Cody: an AI coding assistant that grounds chat, completions, and agent workflows in your entire multi-repo codebase.
Continue
Open-source AI coding agent for VS Code and JetBrains — free to fork since Cursor acquired Continue in January 2026.
Refact.ai
Open-source autonomous AI coding agent that plans, executes, and deploys tasks inside VS Code and JetBrains IDEs.
Featured Head-to-Head Comparisons
Tabby vs Spider Cloud
Choose Tabby if you want a privacy-first AI coding assistant that you can self-host and that now includes an autonomous AI teammate. Choose Spider Cloud if you need a high-speed, low-cost web scraping API with advanced browser AI commands for feeding real-time data into AI agents or RAG pipelines. They solve entirely different problems, so decide based on whether you need code help or web data.
Tabby vs Voyage Ai
If you need an AI coding assistant with real-time code completion and autonomous task execution while maintaining full data control, Tabby is the clear choice with its generous free tier and self-hosting option. If your focus is on building high-accuracy RAG pipelines with domain-specific embedding models (finance, legal) and you have enterprise budget, Voyage AI offers specialized models and low-dimensional embeddings for cost-efficient vector storage, but requires contacting sales for pricing.
Tabby vs Temporal Ai
If you need an AI coding assistant that respects data privacy and runs on your own hardware with autonomous task capabilities, Tabby is the clear choice. If you're building reliable AI agents or microservices that require automatic recovery from failures, Temporal's durable execution platform is unmatched. They solve different problems and can even complement each other.
Replit Agent vs Tabby
Choose Tabby if privacy and control over your code are non-negotiable—you self-host on your GPU, keep data in-house, and want an AI teammate (Pochi) that plans and checks in like a human. Go with Replit Agent if you want to build and deploy full-stack apps from simple prompts, need voice-guided development, and prefer a fully managed cloud IDE with no setup hassle. Tabby suits compliance-heavy teams; Replit wins for rapid prototyping and learning.
Alternatives to Tabby
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Sourcegraph Cody: an AI coding assistant that grounds chat, completions, and agent workflows in your entire multi-repo codebase.
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