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Qwen3.8-Flash-Next performance questioned on R9700 system

By PulseAugur Editorial · [1 sources] ·

A user on Reddit's r/LocalLLaMA subreddit is seeking feedback on the performance of the Qwen3.8-Flash-Next model running on their R9700 system. They are experiencing 863 tokens/s during prefill and 35 tokens/s during decoding with a context length of 230,000 tokens, and are unsure if these speeds are optimal for their hardware configuration. The user has detailed their setup, including the specific model version, backend, CPU, RAM, expert offloading, context settings, and the use of an ngram table, and is asking for advice on potential tuning to improve quality and speed. AI

IMPACT Provides insights into the practical performance limitations and tuning possibilities for local LLM deployments on consumer hardware.

RANK_REASON User-level inquiry about optimizing local LLM performance on specific hardware.

Read on r/LocalLLaMA →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Qwen3.8-Flash-Next performance questioned on R9700 system

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User-level inquiry about optimizing local LLM performance on specific hardware.
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COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/Designer_Elephant227 ·

    Qwen3.8-Flash-Next (5.05bpw + ngram at bf16) exl3 on one r9700: 863 t/s prefill and 35 t/s decode at 230k context (256k max), is that ok or am i missing something?

    <!-- SC_OFF --><div class="md"><p>Hi, i got QFN running on my single r9700 but im not sure if i did everything right to get the best quality and speed out of this setup. Dont want to annoy anybody, maybe someone with the same card can tell me if this looks normal.</p> <p>What i r…

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