llamaperf

Qwen3.8 27B

on NVIDIA RTX 5090 · focus-llama · 200,000 ctx

Tone: positiveNVIDIA hardware
Oct 7, 2026
Throughput
110.0 t/s gen
Quant
Q6_K_XL (GGUF)
KV cache
q8_0

Use cases

codinglong-context

Summary

User reports Qwen3.8-27B at 110+ t/s on a single RTX 5090 with a fork of llama.cpp called focus-llama. Setup uses Q6_K_XL GGUF quantization with q8_0 KV cache, 256k logical context capped to an ~85k physical KV buffer, and adaptive MTP speculative decoding. Speed ranges from about 120 t/s initially down to 60 t/s as context fills; the user cites 100-120 t/s depending on context fullness and says context usage stays at 18-30%.