ollama-lm-studio

GGUF Q4 vs Q5: which quantization should you choose?

Understand the practical difference between Q4 and Q5 for local models and test without downloading the wrong files.

Q4 is the starting point

Q4 is usually the best balance for running local models on normal hardware. It cuts model size heavily and usually keeps acceptable quality for chat, summaries, and simple automation.

Q5 uses more memory and can produce slightly better answers, but it is only worth it when your hardware has headroom.

How to compare in practice

Pick two variants of the same model and run identical prompts:

ollama run llama3.2:3b "Explain quantization in 5 bullets."
ollama run llama3.2:3b "Write a JS function that validates email."

Measure:

• time to first token;
• VRAM/RAM usage;
• answer quality;
• stability with longer prompts.

My recommendation

If you are memory-limited, choose Q4. If Q4 runs comfortably and you want more quality, test Q5. Do not choose Q5 just because it sounds better; choose it because your hardware can handle it without sacrificing too much speed.