llamaperf

Qwen2.5 1.5B

on M2 8GB · llama.cpp

Tone: mixedApple hardware
Sep 18, 2026
Quant
Q2_K (GGUF)
System RAM
8 GB

Use cases

mathsummarization

Summary

User benchmarks quantization accuracy damage on Qwen2.5-1.5B and 0.5B across the Q8 to Q2 ladder, running 24,600 generations on an 8GB M2 Air with llama.cpp and MLX. On the 1.5B model, JSON schema conformance stays at 100% at every rung including Q2, GSM8K arithmetic falls from 56.5% to 19.0% with the first significant drop at Q3, and TriviaQA recall falls from 19% to 9%, breaking only at Q2. Q4 significantly beat Q8 on the 1.5B model in both runtimes (p=0.044 llama.cpp, p=0.015 MLX), while on the 0.5B model MLX 4-bit collapses from 45% to 27.5%. Q2_K is strictly dominated on 0.5B: Q3 gives 40.5% at 122 tok/s versus Q2 at 13.5% and 119 tok/s.