llamaperf

Qwen3.8 27B

on NVIDIA RTX 3090 · llama.cpp · 65,536 ctx

Tone: mixedNVIDIA hardware
Sep 29, 2026
Throughput
31-34 t/s gen · 1080.0 tokens/s prompt processing (prefill)Prompt processing measures input prefill speed; it does not tell you the time to first token.
Quant
UD-Q4_K_XL (GGUF)
KV cache
turbo3
VRAM reported
24 GB

Use cases

agenticcoding

Summary

User reports Qwen 3.8 27B at 31-34 t/s generation and around 1,080 t/s prompt processing on a single RTX 3090 24 GB. Setup is llama.cpp with CUDA, UD-Q4_K_XL quant, 64K context, turbo3 KV cache, 2 parallel slots. User compares four agent configurations: Qwen alone (1/5 scenes right, 26 min, $0), Sonnet 5.5 planning with Qwen coding (2/5, 85 min, $0.67), Qwen planning with Sonnet 5.5 coding (4/5, 14 min, ~$2.77), and Sonnet 5.5 alone (4/5, 9 min, $1.83). A 3060 12 GB was tried first and gave 4-6 t/s with ~7 GB of weights spilling into system RAM. User notes Qwen is a better planner than coder, that thinking budget had to be capped, and that crash checks reported zero errors while some scenes were visibly wrong. One run per setup, described as a field report rather than a benchmark.