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oj748/Phi-4-mini-instruct-Q4_K_M-GGUF overview

Phi 4 mini instruct Q4 K M GGUF This repository contains a GGUF Q4 K M quantized version of Microsoft's Phi 4 mini instruct model. Q4 K M Quantized version can…

ggufbase_model:microsoft/Phi-4-mini-instructbase_model:quantized:microsoft/Phi-4-mini-instructlicense:mitendpoints_compatibleregion:usconversational

Runs locally from ~2.32 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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1 GGUF files detected
Direct downloads for local inference
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phi4-Q4_K_M.ggufGGUFQ4_K_M2.32 GBDownload

Model Details

Model IDoj748/Phi-4-mini-instruct-Q4_K_M-GGUF
Authoroj748
Pipeline
Licensemit
Base modelmicrosoft/Phi-4-mini-instruct
Last modified2026-07-05T12:44:43.000Z

Model README

---

license: mit

base_model: microsoft/Phi-4-mini-instruct

---

Phi-4-mini-instruct Q4_K_M GGUF

This repository contains a GGUF Q4_K_M quantized version of Microsoft's Phi-4-mini-instruct model.

Q4_K_M Quantized version can be downloaded here

The model was converted to the GGUF format and quantized using llama.cpp for local inference as part of my AI-Powered Learning Assistant project.

Base Model

The original model is Microsoft Phi-4-mini-instruct:

microsoft/Phi-4-mini-instruct

Original model: https://huggingface.co/microsoft/Phi-4-mini-instruct

This repository does not contain a model trained from scratch. It contains a converted and quantized version of the original Phi-4-mini-instruct model.

Quantization

  • Format: GGUF
  • Quantization: Q4_K_M
  • Base model: Phi-4-mini-instruct
  • Parameters: 3.8B

Using llama.cpp (https://github.com/ggml-org/llama.cpp) for quantization.

The Q4_K_M quantization was selected after testing different quantized versions of the model for local summarization, flashcard generation, and quiz generation.

It provided a suitable balance between generation quality, inference performance, and memory usage on the development hardware.

Intended Use

This quantized model was prepared for local inference in an AI-Powered Learning Assistant desktop application.

Within the project, the model is used for:

  • Summarization of study material
  • Flashcard generation
  • Quiz generation

The model is executed locally using llama.cpp-compatible tooling.

Acknowledgements

The original Phi-4-mini-instruct model was developed by Microsoft.

Please refer to the original model repository and model card for model details, limitations, responsible AI considerations, and licensing information.

License

The base Phi-4-mini-instruct model is provided under the MIT License. Refer to the original Microsoft model repository for the complete license and usage information.

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