llamaperf

Qwen3.8 125B (6B active) Flash-Next

on NVIDIA RTX 4060 Ti 16GB · llama.cpp · 100,000 ctx

Tone: positiveNVIDIA hardware
Sep 11, 2026
Throughput
18.7 t/s gen · 210.0 tokens/s prompt processing (prefill)Prompt processing measures input prefill speed; it does not tell you the time to first token.
Quant
Q5_K_M (GGUF)
System RAM
64 GB
VRAM reported
8 GB

Use cases

codingcreative-writing

Summary

User reports Qwen3.8 Flash at 18.7 t/s generation on a Ryzen 7700 with 64 GB DDR5 and an RTX 4060 Ti 8 GB. Setup is a custom llama.cpp fork (myllama.cpp) running the 35B MoE model with 6B active parameters, CUDA and Windows specific, with no MTP support. An initial IQ4_XS quant gave 100 t/s prefill and 20 t/s generation, degrading to 15 t/s at 100K context. A switch to Q5_K_M dropped to 15 t/s prefill and 10-13 t/s generation from MMAP page faulting. A four-layer system followed: an unbuffered raw file reader with a RAM buffer for 2 slabs reached 150 t/s prefill, a RAM expert cache with decay factor (55-56 GB, covering 85-95% of requests) gave 14-15 t/s generation, memcpy from cache to buffer during prefill reached 215 t/s prefill, a 2 GB VRAM cache for top experts gave 18.0 t/s generation, and direct IO for embeddings gave 18.7 t/s.