GPTQ (Generative Pre-trained Transformer Quantization)

Post-training quantization method that compresses LLMs to 4-bit with minimal accuracy loss using group-wise quantization.

When to use GPTQ

Use GPTQ when:

• Need to fit large models (70B+) on limited GPU memory
• Want 4× memory reduction with <2% accuracy loss
• Deploying on consumer GPUs (RTX 4090, 3090)
• Need faster inference (3-4× speedup vs FP16)

Use AWQ instead when:

• Need slightly better accuracy (<1% loss)
• Have newer GPUs (Ampere, Ada)
• Want Marlin kernel support (2× faster on some GPUs)

Use bitsandbytes instead when:

• Need simple integration with transformers