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voconly-org/
Qwen3.5-9B-Q4_K_M-GGUF

Name: Qwen3.5-9B-Q4_K_M-GGUF
Availability: InStock

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Qwen3.5-9B-Q4_K_M-GGUF

Model Introduction

This is the GGUF format quantized version of Qwen3.5-9B, suitable for local deployment and inference using llama.cpp and compatible frameworks.

Original Model: Qwen/Qwen3.5-9B

Quantization Information

Quantization Method: Q4_K_M (4-bit Medium Quality)
File Size: ~5.3 GB
Quantization Quality: Balanced between model size and performance, suitable for most use cases

Q4_K_M uses 4-bit quantization for most weights while keeping important layers in higher precision, offering a good trade-off between speed and quality.

Usage

llama.cpp Command Line

bash

# Interactive chat
./llama-cli -m Qwen3.5-9B-Q4_K_M.gguf -ngl 40 -c 8192 --chat-template qwen

# Server mode
./llama-server -m Qwen3.5-9B-Q4_K_M.gguf -ngl 40 -c 8192 --port 8080

Python (llama-cpp-python)

python

from llama_cpp import Llama

llm = Llama(
    model_path="Qwen3.5-9B-Q4_K_M.gguf",
    n_gpu_layers=40,
    n_ctx=8192,
)

response = llm.create_chat_completion(
    messages=[{"role": "user", "content": "Hello, how are you?"}]
)
print(response["choices"][0]["message"]["content"])

Hardware Requirements

Configuration	Minimum RAM	Recommended RAM
CPU-only	12 GB	16 GB
GPU (NVIDIA)	8 GB VRAM	10 GB VRAM

Recommended Hardware:

GPU: NVIDIA RTX 3080 (10GB) or RTX 4070 Ti (12GB) or higher
CPU: Modern multi-core processor with AVX2 support
RAM: 16GB+ system memory

Download Links

ModelScope: Voconly/Qwen3.5-9B-Q4_K_M-GGUF
HuggingFace: Voconly/Qwen3.5-9B-Q4_K_M-GGUF

License

This model follows the original Qwen3.5 license. Please refer to the original model's license for usage terms.

voconly-org/Qwen3.5-9B-Q4_K_M-GGUF