How to use from
llama.cpp
Install from brew
brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf qihoo360/Light-R1-14B-DS-GGUF:Q4_0
# Run inference directly in the terminal:
llama-cli -hf qihoo360/Light-R1-14B-DS-GGUF:Q4_0
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf qihoo360/Light-R1-14B-DS-GGUF:Q4_0
# Run inference directly in the terminal:
llama-cli -hf qihoo360/Light-R1-14B-DS-GGUF:Q4_0
Use pre-built binary
# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf qihoo360/Light-R1-14B-DS-GGUF:Q4_0
# Run inference directly in the terminal:
./llama-cli -hf qihoo360/Light-R1-14B-DS-GGUF:Q4_0
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf qihoo360/Light-R1-14B-DS-GGUF:Q4_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf qihoo360/Light-R1-14B-DS-GGUF:Q4_0
Use Docker
docker model run hf.co/qihoo360/Light-R1-14B-DS-GGUF:Q4_0
Quick Links

Quantized models' evaluation results:

Models AIME24 AIME25
Light-R1-14B-DS 74.0 60.2
Light-R1-14B-DS-Q4_0.gguf (int4) 70.1 54.9
Light-R1-14B-DS-Q8_0.gguf (int8) 71.9 59.4
Light-R1-14B-DS-Q4-KM.gguf (q4-k-m) 70 61.3
Downloads last month
93
GGUF
Model size
15B params
Architecture
qwen2
Hardware compatibility
Log In to add your hardware

4-bit

8-bit

Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for qihoo360/Light-R1-14B-DS-GGUF

Quantized
(8)
this model

Collection including qihoo360/Light-R1-14B-DS-GGUF