llamaperf

Qwen3.8 27B

on NVIDIA RTX 5090 Laptop 24GB · 100,000 ctx

Tone: negativeNVIDIA hardware
Oct 8, 2026
Throughput
37.0 t/s gen
Quant
Q4_K_XL (GGUF)
System RAM
64 GB
VRAM reported
24 GB

Use cases

codingagentic

Summary

User reports Qwen3.8-27B with vision at about 37 tok/s on an RTX 5090 Laptop 24GB with 64GB RAM. Setup is Q4_K_XL at 100K context, tested with the opencode and pi harnesses. User also ran a two-laptop cluster of RTX 5080 Laptop 16GB machines: Qwen3.8-27B Q6_K fine-tuned for coding agents at 67 to 77 tok/s, Qwen3.8-27B Q5_K_XL at 53 tok/s, Qwen3-Coder-Next Q3_K_XL at 48 tok/s, and Qwen3.8-Flash-Next IQ4_XS at 19 tok/s. On the single 5090 laptop, Qwen3-Coder-Next Q3_K_XL reached 55 tok/s and Qwen3.8-Flash-Next with vision IQ4_XS at 262K context reached 20 tok/s. User says none of the local models can complete even minor tasks, filling context without output or producing nonsense, and that hosted GPT-6 and Opus 5.5 handle the same tasks without issue.