How to Launch gemma-4-12B-it-QAT-GGUF on Copilot+ PC Windows

How to Launch gemma-4-12B-it-QAT-GGUF on Copilot+ PC Windows

Running this model locally is fastest when deployed through a PowerShell script.

Please follow the instructions listed below to get started.

1-click setup: the app automatically fetches the large weight files.

The setup file includes a feature that instantly optimizes all configurations.

📤 Release Hash: 583a97b315ffcb729ae7609114c04ab2 • 📅 Date: 2026-06-24
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  • CPU: modern architecture (Zen 3 / Alder Lake minimum)
  • RAM: required: 16 GB absolute minimum for small models
  • Disk Space: free: 80 GB on system drive for scratch space
  • Graphics: stable 30+ tk/s at 4-bit quantization on medium setup

The **gemma-4-12B-it-QAT-GGUF** model is a 12‑billion parameter instruction‑tuned language model designed for high performance and efficiency. It leverages *QAT* (quantized aware training) and the GGUF format to achieve a *balanced trade‑off* between accuracy and inference speed on consumer hardware. The model supports a context window of up to **8192** tokens, enabling it to understand and generate longer passages with coherent reasoning. Benchmarks show it outperforms comparable open models in reasoning and coding tasks while maintaining a modest memory footprint. Below is a quick comparison of its core specifications to illustrate how it stands against other popular open models:

Spec Value
Parameters **12 B**
Context Length **8192** tokens
Quantization QAT‑GGUF
Benchmark (MMLU) 68%
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