llamaperf

Qwen2.5 0.5B

on NVIDIA T4 16GB · Transformers

NVIDIA hardware
Sep 15, 2026
Quant
Q4_K_M (GGUF)
VRAM reported
16 GB

Summary

User measures full next-token distributions before and after quantization on Qwen2.5-0.5B, using 500 probe positions and a float32 CPU reference under transformers 4.57.6 on a T4. GGUF Q4_K_M moves the distribution by 0.0951 mean Hellinger distance and raises perplexity by 5.02%, recovering 67% of the distributional damage and 89% of the perplexity gap relative to an uncalibrated 4-bit group-128 baseline. User notes the 0.5B model size limits conclusions about AWQ and GPTQ, and that 128 calibration samples at 512 tokens is modest.