Qwen3-Coder-30B-A3B-Instruct-f16-GGUF

This is a GGUF-quantized version of the Qwen/Qwen3-Coder-30B-A3B-Instruct language model.

Converted for use with llama.cpp, LM Studio, OpenWebUI, GPT4All, and more.

💡 Key Features of Qwen3-Coder-30B-A3B-Instruct:

Available Quantizations (from f16)

Level	Quality	Speed	Size	Recommendation
Q2_K	Minimal	⚡ Fast	11.30 GB	Only on severely memory-constrained systems.
Q3_K_S	Low-Medium	⚡ Fast	13.30 GB	Minimal viability; avoid unless space-limited.
Q3_K_M	Low-Medium	⚡ Fast	14.70 GB	Acceptable for basic interaction.
Q4_K_S	Practical	⚡ Fast	17.50 GB	Good balance for mobile/embedded platforms.
Q4_K_M	Practical	⚡ Fast	18.60 GB	Best overall choice for most users.
Q5_K_S	Max Reasoning	🐢 Medium	21.10 GB	Slight quality gain; good for testing.
Q5_K_M	Max Reasoning	🐢 Medium	21.70 GB	Best quality available. Recommended.
Q6_K	Near-FP16	🐌 Slow	25.10 GB	Diminishing returns. Only if RAM allows.
Q8_0	Lossless*	🐌 Slow	32.50 GB	Maximum fidelity. Ideal for archival.

💡 Recommendations by Use Case

• 💻 Standard Laptop (i5/M1 Mac): Q5_K_M (optimal quality)
• 🧠 Reasoning, Coding, Math: Q5_K_M or Q6_K
• 🔍 RAG, Retrieval, Precision Tasks: Q6_K or Q8_0
• 🤖 Agent & Tool Integration: Q5_K_M
• 🛠️ Development & Testing: Test from Q4_K_M up to Q8_0

Usage

Load this model using:

• OpenWebUI – self-hosted AI interface with RAG & tools
• LM Studio – desktop app with GPU support
• GPT4All – private, offline AI chatbot
• Or directly via llama.cpp

Each quantized model includes its own README.md and shares a common MODELFILE.

Author

👤 Geoff Munn (@geoffmunn)
🔗 Hugging Face Profile

Disclaimer

This is a community conversion for local inference. Not affiliated with Alibaba Cloud or the Qwen team.