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Overview
Tabby is an open-source, self-hosted AI coding assistant offering IDE extensions and model serving. Key capabilities observed in the documentation and marketing site include fast, context-aware code completion, an in-IDE Answer Engine/Inline Chat, Data Connectors/Context Providers to ingest project docs/configs/APIs, model interoperability (references to CodeLlama, StarCoder, CodeGen and others), and EngOps tooling for deployment, backups, and telemetry controls. The project emphasizes transparency and local-first operation (self-hosted or on-prem) while providing flexible cloud deployment options and a Tabby Cloud usage-based offering. Documentation includes quick-start installation notes (including CUDA 11+ requirement for GPU acceleration on Windows), cloud-deployment references (Modal, BentoML, SkyPilot) that mention supported GPUs (T4, L4, A100), an administration backup page noting default SQLite DB location ($HOME/.tabby/ee/db.sqlite), and a models registry with a public leaderboard for benchmarks. Marketing/pricing content lists Community (free/local-first), Team (per-user subscription — example shown ~ $19/user/month on the marketing page), Enterprise (custom, SSO and advanced security), and Tabby Cloud (usage-based billing with some free monthly credits and budget controls). The docs-hosted pricing page returned 404; the marketing pricing page contains some inconsistent/garbled text and should be verified with sales before relying on exact numbers.
Key Features
Context-aware code completion
Fast, context-aware code completion integrated into IDE extensions for productivity improvements.
In-IDE Answer Engine and Inline Chat
Answer Engine and Inline Chat capabilities within the IDE to ask questions and get context-aware responses.
Data Connectors / Context Providers
Connectors and context providers to pull project documentation, configuration files, and API specs into the model context.
Model interoperability
Supports multiple models (marketing/docs reference CodeLlama, StarCoder, CodeGen and others) for flexible model choices.
IDE extensions + model serving
Architecture includes IDE extensions and model-serving components for self-hosted or cloud deployment.
EngOps and administration tooling
Tools and documentation for deployment, backups, telemetry controls, and operational management.
Who Can Use This Tool?
- Individual developers:Local-first AI coding assistant for individual developers; Community plan free, up to 5 users referenced.
- Teams:Small to medium teams seeking per-user paid collaboration features and cloud or self-hosted deployment.
- Enterprises:Large organizations requiring SSO, advanced security, custom contracts, and operational controls.
Pricing Plans
Free, local-first Community plan intended for individuals and small teams. Marketing page references up to 5 users for this plan.
- ✓Local-first / self-hosted use
- ✓Free community access
- ✓Up to 5 users referenced on marketing page
Paid per-user Team plan. The marketing page shows an example ~ $19/user/month; pricing page and labels contain inconsistencies — verify with sales.
- ✓Per-user billing
- ✓Collaboration features (as marketed)
- ✓Hosted or self-hosted options implied
Custom Enterprise offering with unlimited users, SSO, and advanced security. Contact sales for details and official pricing.
- ✓Unlimited users (marketing claim)
- ✓SSO and advanced security
- ✓Custom contract and support
Usage-based cloud offering (Tabby Cloud) with usage billing, some free monthly credits and budget controls as described on the marketing page. Exact billing details should be confirmed with sales.
- ✓Usage-based billing
- ✓Free monthly credits referenced
- ✓Budget controls
Pros & Cons
✓ Pros
- ✓Open-source and self-hosted allowing local-first and on-prem deployments
- ✓IDE extensions with context-aware code completion and Inline Chat/Answer Engine
- ✓Supports multiple models (CodeLlama, StarCoder, CodeGen references) for flexibility
- ✓Documentation covers installation, backups, cloud deployments, and model benchmarks
- ✓Cloud deployment guides (Modal, BentoML, SkyPilot) and mentions supported GPUs
✗ Cons
- ✗Docs subdomain pricing page returned a 404; marketing pricing page contains inconsistent/garbled text — pricing should be verified with sales
- ✗Self-hosted setups require operational work (e.g., GPU/CUDA requirements for acceleration — Windows install notes require CUDA 11+)
- ✗Some marketing content appears inconsistent; do not rely on shown example prices without confirmation
- ✗No explicit mobile app information found in the inspected pages
Compare with Alternatives
| Feature | Tabby | Aider | Cline |
|---|---|---|---|
| Pricing | $19/month | N/A | N/A |
| Rating | 8.4/10 | 8.3/10 | 8.1/10 |
| Deployment Flexibility | Yes | Partial | Partial |
| Local-First Support | Yes | Partial | Yes |
| Model Interoperability | Yes | Yes | Yes |
| IDE Integration Depth | Deep IDE extensions and inline chat | Editor and CLI integration | Limited IDE integration |
| Agent Automation | Partial | Yes | Yes |
| Context Connectors | Yes | Yes | Yes |
| EngOps Tooling | Yes | Partial | Yes |
| Observability & Audit | Yes | Partial | Yes |
Related Articles (5)
Overview of TabbyML's Tabby, a self-hosted AI coding assistant, and its place in a growing ecosystem of local-first AI tools.
A chronological roundup of Tabby’s latest features, integrations, and deployment updates from 2023–2024.
Incremental decoding, streaming, and retrieval-augmented coding in Tabby, with deployment tips and roadmap.
GitHub release notes for TabbyML/tabby, featuring a new nightly build and 0.31.x patches with sharded indexing and SQLite improvements.
Tabby is an open-source, self-hosted AI coding assistant with OpenAPI, GPU support, and Docker-based quickstart.
