Qwen3.8 27B
on NVIDIA DGX Spark · llama.cpp · 16,384 ctx
Summary
User benchmarks a llama.cpp PR that fuses FFN gate/up matmuls and GLU in MMQ, on a DGX Spark (GB10) and an RTX 5090.
Setup is llama.cpp with llama-bench, -ngl 999, flash attention on, 16384-token prompts, F16 KV cache, batch 2048, 5 repetitions.
On the DGX Spark, Qwen3.8-27B Q4_K_M prompt processing rises from 840.1 to 899.9 tok/s (+7.1%). On the RTX 5090 the same model and quant goes from 3688.4 to 3790.9 tok/s. The table also covers Qwen3.6-27B and Llama-3.1-8B across Q4_K_M, Q5_K_M, Q6_K, Q8_0 and IQ4_XS; only prompt processing was measured (-n 0).