This is a 4-bit quantized GGUF version of Google's Gemma-4 2B (E2B) instruction-tuned model. The QAT (Quantization Aware Training) and GGUF format allow efficient local inference using tools like llama.cpp. It is designed for on-device or local LLM applications.
Gemma 4 E2B It Qat Q4 0 sits in PulseGate's Text generation category. It focuses on running powerful instruction-tuned language models locally with reduced memory requirements. It is built as an open-source project for developers. The project is open source (Open Source). Gemma 4 E2B It Qat Q4 0 is available on the web, the command line, and API.
Google builds and maintains Gemma 4 E2B It Qat Q4 0, and it first shipped in 2025. The category is crowded — PulseGate's index counts 25 comparable projects. Key capabilities include Quantized Model, Instruction Tuned, and GGUF Format.
Summary written by a language model from the project’s public pages.
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