DhruvalLabs / phi-2-GGUF

huggingface.co
Total runs: 189
24-hour runs: 3
7-day runs: -9
30-day runs: 114
Model's Last Updated: June 17 2026
text-generation

Introduction of phi-2-GGUF

Model Details of phi-2-GGUF

phi-2 — GGUF Quantizations

Model on HF Original Model quant-kit

Quantized GGUF versions of microsoft/phi-2

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

Quantized by Dhptl on June 17, 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-2-Q2_K.gguf 1.03 GB ~2.5 GB Q2_K ⭐ Extreme compression, significant quality loss.
phi-2-Q3_K_L.gguf 1.47 GB ~3.0 GB Q3_K_L ⭐⭐⭐ Slightly better than Q3_K_M, still a compromise.
phi-2-Q3_K_M.gguf 1.33 GB ~2.8 GB Q3_K_M ⭐⭐⭐ Very small file. Quality drop noticeable.
phi-2-Q3_K_S.gguf 1.16 GB ~2.7 GB Q3_K_S ⭐⭐ Very high compression, high quality loss.
phi-2-Q4_K_M.gguf 1.62 GB ~3.1 GB Q4_K_M ✅ Recommended ⭐⭐⭐⭐ Best balance of size and quality. Recommended for most users.
phi-2-Q4_K_S.gguf 1.51 GB ~3.0 GB Q4_K_S ⭐⭐⭐½ Good speed/size balance, slight quality loss.
phi-2-Q5_K_M.gguf 1.87 GB ~3.4 GB Q5_K_M ⭐⭐⭐⭐½ Better quality than Q4, slightly larger. Great if you have the RAM.
phi-2-Q5_K_S.gguf 1.80 GB ~3.3 GB Q5_K_S ⭐⭐⭐⭐ Large but accurate.
phi-2-Q6_K.gguf 2.13 GB ~3.6 GB Q6_K ⭐⭐⭐⭐⭐ Near-perfect quality, very large.
phi-2-Q8_0.gguf 2.75 GB ~4.3 GB Q8_0 ⭐⭐⭐⭐⭐ Closest to original quality. Use when RAM is not a concern.
💡 Which file should I download?
  • Most users: phi-2-Q4_K_M.gguf — best balance of size and quality
  • High RAM (32GB+): phi-2-Q8_0.gguf — near-original quality
  • Low RAM (8GB): phi-2-Q3_K_M.gguf — fits in 8GB with room to spare

⚡ Speed Benchmarks

Run python benchmark.py --model phi-2 to generate speed results.


🧠 Quality Benchmarks

Run kaggle_bench.ipynb on Kaggle to benchmark this model.


🚀 How to Use
Ollama
ollama run dhptl/phi-2
LM Studio / Jan / Open WebUI

Search for Dhptl/phi-2 in the model browser.

llama.cpp CLI
# Download the binary from https://github.com/ggerganov/llama.cpp/releases
./llama-cli \
  -m phi-2-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-2-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-2-GGUF on huggingface.co

189
Total runs
3
24-hour runs
-3
3-day runs
-9
7-day runs
114
30-day runs

More Information About phi-2-GGUF huggingface.co Model

More phi-2-GGUF license Visit here:

https://choosealicense.com/licenses/mit

phi-2-GGUF huggingface.co

phi-2-GGUF huggingface.co is an AI model on huggingface.co that provides phi-2-GGUF's model effect (), which can be used instantly with this DhruvalLabs phi-2-GGUF model. huggingface.co supports a free trial of the phi-2-GGUF model, and also provides paid use of the phi-2-GGUF. Support call phi-2-GGUF model through api, including Node.js, Python, http.

DhruvalLabs phi-2-GGUF online free

phi-2-GGUF huggingface.co is an online trial and call api platform, which integrates phi-2-GGUF's modeling effects, including api services, and provides a free online trial of phi-2-GGUF, you can try phi-2-GGUF online for free by clicking the link below.

DhruvalLabs phi-2-GGUF online free url in huggingface.co:

https://huggingface.co/DhruvalLabs/phi-2-GGUF

phi-2-GGUF install

phi-2-GGUF is an open source model from GitHub that offers a free installation service, and any user can find phi-2-GGUF on GitHub to install. At the same time, huggingface.co provides the effect of phi-2-GGUF install, users can directly use phi-2-GGUF installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

phi-2-GGUF install url in huggingface.co:

https://huggingface.co/DhruvalLabs/phi-2-GGUF

Url of phi-2-GGUF

Provider of phi-2-GGUF huggingface.co

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