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Llama.cpp uses CPU despite available VRAM, user seeks solution

By PulseAugur Editorial · [1 sources] ·

A user running the Qwen3.8:27b model via llamacpp on a Windows Server with an NVIDIA A5000 GPU is experiencing unexpected CPU usage during inference. Despite the GPU being nearly maxed out with VRAM utilization at 22.6GB, the system intermittently engages the CPU. The user is seeking to understand the cause of this behavior and how to prevent it, as their command line arguments suggest offloading the entire model to the GPU. AI

IMPACT Troubleshooting guide for users experiencing similar performance issues with local LLM deployments.

RANK_REASON User inquiry about optimizing a specific software tool's performance.

Read on r/LocalLLaMA →

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

Llama.cpp uses CPU despite available VRAM, user seeks solution

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User inquiry about optimizing a specific software tool's performance.
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COVERAGE [1]

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

    Why is LlamaCpp using CPU if VRAM is available?

    <!-- SC_OFF --><div class="md"><p>I am running Qwen3.8:27b with the following command on Windows Server:</p> <p><code> llama.exe serve -hf bartowski/Qwen3.8-27B-GGUF:Q4_K_L -ngl 99 -c 65536 --port 11434 </code></p> <p>The server has an NVidia A5000 with 24GB of VRAM. When the mod…

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