The llama.cpp project released version b10726, which introduces significant performance optimizations for processing large batch sizes in IQ quantized models. The primary update leverages AVX2 instructions to accelerate grid IQ quants through batched GEMM operations.

  • Batched GEMM implementation for grid IQ quants
  • Vectorization of IQ panel decode with a lowered threshold for speedup
  • Introduction of the ggml_gemm_iqp_8x8_q8_K_p4 kernel and removal of the gather buffer
  • Single-source gather layout, gate bias, and vectorized interleave for IQ panels
  • Addition of NUMA fallback support and 10-row batch tests for IQP coverage

This release provides faster inference capabilities for users running IQ models on compatible hardware.