Which is more popular, harbor or TextGen?

TextGen has more GitHub stars (47,721 vs 3,237).

Which is more actively developed, harbor or TextGen?

harbor had more commits in the last 90 days (369 vs 1).

Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.

Side-by-side comparison of two AI agent tools

TextGen is growing faster: +215 GitHub stars in the last 30 days vs +110 for harbor.
Pick harbor for: one command brings a complete pre-wired LLM stack with hundreds of services to explore. Pick TextGen for: the original local LLM interface.

From GitHub data refreshed daily.

harboropen-source

One command brings a complete pre-wired LLM stack with hundreds of services to explore.

The original local LLM interface. Text, vision, tool-calling, training, and more. 100% offline.

+Complete offline operation with zero telemetry ensures maximum privacy and data security
+Multiple backend support (llama.cpp, Transformers, ExLlamaV3, TensorRT-LLM) with hot-swapping capabilities
+Comprehensive feature set including vision, tool-calling, training, and image generation in one interface

-Requires significant local hardware resources (GPU/CPU) for optimal performance
-Full feature set installation may be complex compared to portable GGUF-only builds
-No cloud-based fallback options when local hardware is insufficient

•Privacy-sensitive organizations needing local AI without data leaving premises
•Researchers and developers fine-tuning custom models with LoRA training
•Content creators requiring offline multimodal AI for text, vision, and image generation

Which is more popular, harbor or TextGen?: TextGen has more GitHub stars (47,721 vs 3,237).
Which is more actively developed, harbor or TextGen?: harbor had more commits in the last 90 days (369 vs 1).
Should I use harbor or TextGen?: Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.