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Dual 3090 GPUs achieve 1600+ tps with Qwen 3.6 27B by switching split modes

By PulseAugur Editorial · [1 sources] ·

A user on Reddit's r/LocalLLaMA community shared their experience optimizing performance for the Qwen 3.6 27B model on a dual 3090 GPU setup. Initially, using `--split-mode tensor` resulted in prompt processing occurring on the CPU, leading to a low tokens-per-second rate of around 400. After extensive testing, the user discovered that switching to `--split-mode layer` significantly improved performance, boosting tokens-per-second to over 1600, although it slightly reduced the model's overall throughput. AI

IMPACT Demonstrates how configuration changes can drastically improve inference speed for local LLM deployments.

RANK_REASON User-level optimization of existing hardware and software for a specific model.

Read on r/LocalLLaMA →

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

Dual 3090 GPUs achieve 1600+ tps with Qwen 3.6 27B by switching split modes

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0 / 100
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Tool
User-level optimization of existing hardware and software for a specific model.
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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infra, product
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High
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62 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

Full methodology in our editorial standards.

COVERAGE [1]

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

    Dual 3090 setup: 400 pp t/s to 1600 pp t/s on Qwen 3.6 27B... with slightly lower tps.

    <!-- SC_OFF --><div class="md"><p>First of all, my setup:</p> <pre><code>Ryzen 9 5950x DDR4 3200Mhz 64gb (2x32) Dual 3090s, no NVLINK </code></pre> <p>Runtime:</p> <pre><code>llama.cpp Nvidia Drivers 610 Windows 11 25H2 Qwen 3.6 27B Q8 </code></pre> <p>I've been using llama-serve…

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