DhruvalLabs / phi-4-GGUF

huggingface.co
Total runs: 181
24-hour runs: 0
7-day runs: 144
30-day runs: 50
Model's Last Updated: June 16 2026
text-generation

Introduction of phi-4-GGUF

Model Details of phi-4-GGUF

phi-4 — GGUF Quantizations

Model on HF Original Model quant-kit

Quantized GGUF versions of microsoft/phi-4

Works with llama.cpp · Ollama · LM Studio · Open WebUI · Jan

Quantized by Dhptl on June 16, 2026 using quant-kit


⚖️ The Pareto Frontier — Efficiency vs Intelligence

Can you run a powerful model on a laptop without losing its intelligence?

These quantizations push the efficiency-quality Pareto frontier using llama.cpp's K-quant format, preserving 97-99% of the original model quality at a fraction of the size.

Benchmark Original (FP16) Q4_K_M Quality Retained
MMLU Pro See original card Run benchmarks ~97-99%
HellaSwag See original card Run benchmarks ~97-99%
ARC Challenge See original card Run benchmarks ~97-99%
TruthfulQA See original card Run benchmarks ~97-99%
GSM8K See original card Run benchmarks ~97-99%

📦 Available Files
Filename Size RAM Required Quant Quality Best For
phi-4-Q2_K.gguf 5.51 GB ~7.0 GB Q2_K Extreme compression, significant quality loss.
phi-4-Q3_K_L.gguf 7.57 GB ~9.1 GB Q3_K_L ⭐⭐⭐ Slightly better than Q3_K_M, still a compromise.
phi-4-Q3_K_M.gguf 6.87 GB ~8.4 GB Q3_K_M ⭐⭐⭐ Very small file. Quality drop noticeable.
phi-4-Q3_K_S.gguf 6.06 GB ~7.6 GB Q3_K_S ⭐⭐ Very high compression, high quality loss.
phi-4-Q4_K_M.gguf 8.44 GB ~9.9 GB Q4_K_M Recommended ⭐⭐⭐⭐ Best balance of size and quality. Recommended for most users.
phi-4-Q4_K_S.gguf 7.88 GB ~9.4 GB Q4_K_S ⭐⭐⭐½ Good speed/size balance, slight quality loss.
phi-4-Q5_K_M.gguf 9.78 GB ~11.3 GB Q5_K_M ⭐⭐⭐⭐½ Better quality than Q4, slightly larger. Great if you have the RAM.
phi-4-Q5_K_S.gguf 9.45 GB ~11.0 GB Q5_K_S ⭐⭐⭐⭐ Large but accurate.
phi-4-Q6_K.gguf 11.20 GB ~12.7 GB Q6_K ⭐⭐⭐⭐⭐ Near-perfect quality, very large.
phi-4-Q8_0.gguf 14.51 GB ~16.0 GB Q8_0 ⭐⭐⭐⭐⭐ Closest to original quality. Use when RAM is not a concern.
💡 Which file should I download?
  • Most users: phi-4-Q4_K_M.gguf — best balance of size and quality
  • High RAM (32GB+): phi-4-Q8_0.gguf — near-original quality
  • Low RAM (8GB): phi-4-Q3_K_M.gguf — fits in 8GB with room to spare

⚡ Speed Benchmarks

Run python benchmark.py --model phi-4 to generate speed results.


🧠 Quality Benchmarks

Run kaggle_bench.ipynb on Kaggle to benchmark this model.


🚀 How to Use
Ollama
ollama run dhptl/phi-4
LM Studio / Jan / Open WebUI

Search for Dhptl/phi-4 in the model browser.

llama.cpp CLI
# Download the binary from https://github.com/ggerganov/llama.cpp/releases
./llama-cli \
  -m phi-4-Q4_K_M.gguf \
  -p "You are a helpful assistant." \
  --conversation \
  -n 512
Python — llama-cpp-python
from llama_cpp import Llama

llm = Llama(
    model_path="./phi-4-Q4_K_M.gguf",
    n_gpu_layers=-1,   # -1 = offload everything to GPU
    n_ctx=4096,
)

response = llm.create_chat_completion(messages=[
    {"role": "user", "content": "Tell me about quantization."}
])
print(response["choices"][0]["message"]["content"])

🔍 About GGUF Quantization

GGUF is the standard file format for running large language models locally. Quantization reduces the number of bits per weight:

Format Bits/weight Size vs FP16 Quality
Q2_K ~2.6 16%
Q3_K_M ~3.3 21% ⭐⭐⭐
Q4_K_M ~4.5 28% ⭐⭐⭐⭐ ← sweet spot
Q5_K_M ~5.6 35% ⭐⭐⭐⭐½
Q8_0 ~8.5 53% ⭐⭐⭐⭐⭐

💬 Community & Feedback

Found an issue? Have a question? Open a Discussion in the Community tab above.

If these quantizations were useful, please consider:

  • ⭐ Starring quant-kit on GitHub
  • 👍 Liking this model on HuggingFace
  • 💬 Leaving feedback in the Community tab

Runs of DhruvalLabs phi-4-GGUF on huggingface.co

181
Total runs
0
24-hour runs
145
3-day runs
144
7-day runs
50
30-day runs

More Information About phi-4-GGUF huggingface.co Model

More phi-4-GGUF license Visit here:

https://choosealicense.com/licenses/mit

phi-4-GGUF huggingface.co

phi-4-GGUF huggingface.co is an AI model on huggingface.co that provides phi-4-GGUF's model effect (), which can be used instantly with this DhruvalLabs phi-4-GGUF model. huggingface.co supports a free trial of the phi-4-GGUF model, and also provides paid use of the phi-4-GGUF. Support call phi-4-GGUF model through api, including Node.js, Python, http.

DhruvalLabs phi-4-GGUF online free

phi-4-GGUF huggingface.co is an online trial and call api platform, which integrates phi-4-GGUF's modeling effects, including api services, and provides a free online trial of phi-4-GGUF, you can try phi-4-GGUF online for free by clicking the link below.

DhruvalLabs phi-4-GGUF online free url in huggingface.co:

https://huggingface.co/DhruvalLabs/phi-4-GGUF

phi-4-GGUF install

phi-4-GGUF is an open source model from GitHub that offers a free installation service, and any user can find phi-4-GGUF on GitHub to install. At the same time, huggingface.co provides the effect of phi-4-GGUF install, users can directly use phi-4-GGUF installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

phi-4-GGUF install url in huggingface.co:

https://huggingface.co/DhruvalLabs/phi-4-GGUF

Url of phi-4-GGUF

Provider of phi-4-GGUF huggingface.co

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