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Qwen3.6-35B-A3B model sees 2.36x prompt processing boost via CPU offload

A user on Reddit shared a method for optimizing the Qwen3.6-35B-A3B model on an RTX 3090 GPU. By offloading eight Mixture-of-Experts (MoE) layers to the CPU, they were able to free up VRAM. This allowed for an increase in batch size and micro-batch size, resulting in a 2.36x improvement in prompt processing speed while generation speed remained largely unchanged. AI

IMPACT Demonstrates a technique for improving LLM performance on consumer hardware by strategically offloading components.

RANK_REASON User-shared optimization technique for a specific model and hardware.

Read on r/LocalLLaMA →

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

Qwen3.6-35B-A3B model sees 2.36x prompt processing boost via CPU offload

COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/Longjumping-Music638 ·

    Auto-fit vs tuned MoE offload: 564 → 1330 pp tok/s, unchanged decode (Qwen3.6-35B-A3B Q6 / RTX 3090)

    <!-- SC_OFF --><div class="md"><p>TL;DR: On a Qwen3.6-35B-A3B Q6 setup sized for 64K context on a 24GB RTX 3090, spilling eight MoE expert layers to CPU freed enough VRAM to increase <code>-b</code> from 512 to 1024 and <code>-ub</code> from 128 to 512.</p> <p>Prompt processing i…