How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "zooai/coder-1-gguf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zooai/coder-1-gguf",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
Use Docker
docker model run hf.co/zooai/coder-1-gguf:Q3_K_M
Quick Links

Zoo Coder-1 GGUF (Quantized Coding Model)

Zoo AI 501(c)(3)

Overview

Zoo Coder-1 GGUF provides quantized versions of our enterprise-grade coding AI model. These GGUF-formatted models enable efficient deployment across various hardware configurations while maintaining excellent coding capabilities.

Model Details

  • Base: Qwen3-Coder with A3B technology
  • Format: GGUF quantized
  • Context: 32K tokens (extensible to 128K)
  • Languages: Python, JavaScript, TypeScript, Go, Rust, Java, C++, and 50+ more

Available Quantizations

Variant Size RAM Required Use Case
Q2_K ~2GB 4GB Edge devices, prototyping
Q3_K_M ~2.5GB 5GB Mobile, lightweight servers
Q4_K_M ~3.2GB 6GB Recommended - Best balance
Q5_K_M ~4GB 7GB High-quality production
Q6_K ~5GB 8GB Maximum quality

Quick Start

With llama.cpp

./main -m Q4_K_M-GGUF/Q4_K_M-GGUF-00001-of-00032.gguf \
  -p "Write a Python function to calculate fibonacci numbers"

With Zoo Desktop

zoo model download coder-1-gguf

About Zoo AI

Zoo Labs Foundation Inc is a 501(c)(3) nonprofit organization pioneering accessible AI infrastructure.

License

Apache 2.0

Downloads last month
23
GGUF
Model size
480B params
Architecture
qwen3moe
Hardware compatibility
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