HuggingFace

gemma-4-31B-it-GGUF

gemma-4-31B-it-GGUF

Running this model locally is fastest when deployed through Docker.

Use the instructions provided below to complete the setup.

The installer auto-downloads and deploys the entire model pack.

There is no manual tuning required; the builder will automatically deploy the best matching configuration.

🔗 SHA sum: 721dd77fb1874c666c893929e8d8084b | Updated: 2026-06-27



  • Processor: next-gen chip for heavy context processing
  • RAM: 48 GB needed to prevent memory swapping to disk
  • Storage:100 GB free space for HuggingFace cache folder
  • Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration

The **gemma-4-31B-it-GGUF** model represents a significant advancement in open‑source language models, combining a 31‑billion parameter architecture with instruction‑following capabilities. Built on the Gemma family, it leverages optimized GGUF quantization to deliver fast inference while maintaining high accuracy on a wide range of tasks. The model excels in multilingual understanding, code generation, and reasoning, making it suitable for both research and production environments. Its lightweight footprint enables deployment on consumer hardware without sacrificing performance, thanks to efficient memory usage and streamlined token processing. Below is a quick comparison of key specifications that highlight its competitive edge:

Metric Value
Parameters 31 B
Quantization GGUF
Max Context 8K

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