A GGUF quantized model using Quantization-Aware Training (QAT) of the Gemma-4-26B-A4B instruct variant. Published by Unsloth, it offers a balance between model size, speed, and performance for local deployment with llama.cpp and similar engines.
In the Foundation models & chat space, Gemma 4 26B A4B It Qat takes a focused approach. It focuses on running a large Gemma 4 model efficiently on standard hardware with minimal quality loss. It is built as an open-source project for developers. Gemma 4 26B A4B It Qat is open source under the Apache-2.0 license. Gemma 4 26B A4B It Qat is available on the web, the command line, and API.
Behind Gemma 4 26B A4B It Qat is Unsloth, and the product first shipped in 2023. Development happens publicly on GitHub with 68.7k stars and 1.2k commits in the last 90 days. The category is crowded — PulseGate's index counts 25 comparable apps. Key capabilities include GGUF Quantization, QAT, and Local Inference.
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