llamaperf

Qwen3.8 27B

on 2× NVIDIA RTX Pro 6000 Blackwell · SGLang · 262,144 ctx

Tone: mixedNVIDIA hardware
Sep 7, 2026
Throughput
150.0 t/s gen
Quant
FP8
KV cache
FP8

Use cases

agenticlong-context

Summary

User reports Qwen 3.8 27B FP8 on two RTX 6000 Pro GPUs with sglang at 150 tk/sec, but tasks take 12x longer than Claude Opus 5. BF16 on the primary card with FP8 offloading took 3 hours versus 1h45m for FP8. Context lengths tested are 256k, 128k (too small) and 500k (faster despite being unsupported). A skill that reads large documentation files hits 80k context before starting. The user compares against Claude Code, Pi Code, Qwen Code and Hermes, and uses ChatGPT 5.6 high for testing.