This repository contains GGUF quantized weights for Gemma 4 31B (instruction-tuned) created using Unsloth's QAT (Quantization-Aware Training) pipeline. It enables efficient local inference of a very large model on CPUs and GPUs with reduced memory requirements. The model is fully open and compatible with llama.cpp and other GGUF runtimes.
Gemma 4 31B It Qat is a Foundation models & chat project. It focuses on running a large instruction-tuned language model efficiently on consumer hardware. It is built as an open-source project for developers. The project is open source (Apache-2.0). It ships for the web, the command line, and API.
Unsloth builds and maintains Gemma 4 31B It Qat, and it first shipped in 2023. Development happens publicly on GitHub with 69.2k stars and 1.4k commits in the last 90 days. It competes in a saturated segment with 25 similar apps in PulseGate's index. Key capabilities include Instruction Tuning, Quantized GGUF, and Local Inference. It exposes integrations via a public API.
Summary written by a language model from the project’s public pages.
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