A text-in, text-out model running on full ternary quantization — meaning its weights use three values instead of the typical binary or floating-point representations. This architectural choice keeps the model compact and efficient at 27 billion parameters, though specific capability details beyond the quantization format are limited. It ships in GGUF format, making it straightforward to run locally with common inference tools.