To get this model running locally in no time, utilize the built-in WSL tools.
Refer to the action plan below to initialize the model.
All large files and heavy weights are downloaded automatically by the script.
The setup file includes a feature that instantly optimizes all configurations.
gemma-4-26B-A4B-it-qat-GGUF is a large language model built on the Gemma architecture with 26 billion parameters. It employs *QAT* techniques to improve inference efficiency while maintaining high performance. The model offers an 8K token context window, enabling detailed reasoning and long‑form generation. Benchmarks demonstrate *competitive* results across multilingual tasks, especially in code generation and factual QA. Its GGUF format ensures broad compatibility with inference engines and reduces memory usage for deployment.
| Parameters | 26 B |
| Context Length | 8K tokens |
| Quantization | QAT (GGUF) |
| Architecture | Gemma‑4 |
| Primary Use | Text generation, code, QA |
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