Create

Sign in to ReadmeX

or

How we handle your data: Privacy Policy

ReadmeX

Your AI reading companion

What would you like to catch up on?

Pick a briefing, or ask your own question.

Your community and people briefings stay personal to you.

Story

4x Radeon R9700 runs Qwen3.8 Flash-Next at ~190 tok/s, 6,800 tok/s prefill

AI summary

A Reddit user (/u/Anarchaotic) posted initial benchmarks for a four-GPU Radeon R9700 system (3x Gigabyte, 1x XFX, all power-limited to 210W) running Radiance v1.17.0 with a qwen3.8-next-flash-fp8-iq4r-moe.rad MoE model on Ubuntu 26.04.1 and ROCm 10.1. Client-side measurements show one user writing at about 190 tok/s, aggregate prefill of about 6,800 tok/s regardless of user count, and agent follow-up turns returning the first token in 0.2-2.5 s at 80-225 tok/s per user with 94-99% prefix-cache hits. The reported worst case of eight simultaneous fresh 128K prompts took about 151 seconds for the first token, while the two middle cards reached 91 C hotspot and 92 C memory during prefill.

In-depth insight

It provides concrete community-measured data on what a four-R9700, ROCm-based local inference server can deliver for long-context, multi-user agent workloads, including the trade-off between cold prefill latency and fast cached follow-ups.

#Qwen3.8 Flash-Next#Radiance#Radeon AI PRO R9700#AMD ROCm#Qwen#Ubuntu

Original · 2 min readRead the original
Group chat

No comments yet. Start the conversation.