This is a community-quantized GGUF version of Google's Gemma 4 26B instruction-tuned model. It enables efficient local execution on CPUs and GPUs using tools like LM Studio, llama.cpp, and Ollama. The model supports text generation and conversational tasks while significantly reducing memory requirements through quantization.
Gemma 4 26B A4B It QAT sits in PulseGate's Quantised & converted weights category. It focuses on running large language models efficiently on consumer hardware without cloud dependency. It is built as an open-source project for developers. Gemma 4 26B A4B It QAT is open source under the MIT license. It ships for the web and the command line, and it can be self-hosted.
lmstudio-community builds and maintains Gemma 4 26B A4B It QAT, and it first shipped in 2023. The project is developed in the open on GitHub with 121.2k stars and 1.2k commits in the last 90 days. It competes in a saturated segment with 25 similar projects in PulseGate's index. Key capabilities include quantized weights, GGUF format, and instruction tuned.
Summary written by a language model from the project’s public pages.
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