harbor vs textgen
Local AI stacks and model interfaces compared
harbor coordinates connected local AI services through Docker Compose, while textgen provides a desktop and web interface for running local language models. harbor focuses on bringing multiple services together; textgen focuses on model use, generation, and API access in one application.
harbor: Orchestrate a Local LLM Stack
Harbor is a CLI and companion app for bringing up connected local LLM services through Docker Compose. It suits people exploring self-hosted models and AI tools who want shared configuration instead of wiring each service by hand.
textgen: Run Local Language Models in a Desktop App
TextGen is a private desktop and web interface for running local language models, with support for chat, vision, tools, and compatible APIs. It suits people who want to use and manage models on their own hardware.
| harbor | textgen | |
|---|---|---|
| Language | Python | Python |
| License | Apache-2.0 | AGPL-3.0 |
| Stars | 3.2k | 47.7k |
| Forks | 229 | 6k |
| Last analyzed | Oct 7, 2026 | Oct 3, 2026 |
Key differences
- harbor starts configured combinations of backends, frontends, and supporting services; textgen centers on chat, generation, and model management in its interface.
- harbor relies on Docker Compose to coordinate services, while textgen offers desktop and browser-based use with installation paths suited to different backends and hardware.
- harbor includes adapters for supported coding and agent CLIs; textgen offers local OpenAI- and Anthropic-compatible APIs, custom tools, and MCP support.
- Both projects use Python, but harbor is licensed under Apache-2.0 and textgen under AGPL-3.0.
- harbor is aimed at local experimentation and development, not production deployment; textgen supports local use cases including offline chat, API endpoints, fine-tuning, and image generation, subject to setup and hardware.
- textgen has more reported stars and forks than harbor, while harbor's considerations note concentrated contributions and long median issue resolution times.
Choose harbor if you…
- want to bring local models, interfaces, and supporting AI services together through Docker Compose.
- need a CLI for managing service configuration, logs, model downloads, or supported coding-agent workflows.
- are prototyping a local research or automation stack with services such as web search, n8n, or MCP tools.
Choose textgen if you…
- want a desktop or browser interface for local chat and text generation across several inference backends.
- need local API endpoints compatible with OpenAI or Anthropic formats, including tool calling.
- want to explore document and image inputs, custom tools, LoRA fine-tuning, or image generation, and can configure the installation for your hardware.
Compare the numbers side by side, or add more projects
This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.