Qwen3.6 and Gemma4 LLM performance benchmarks detailed on triple-GPU setup

A user on Reddit's r/LocalLLaMA subreddit shared performance benchmarks for various large language models, including Qwen3.6 and Gemma4, running on a system with three GPUs (GTX 1080 Ti and two P102-100s) totaling 31GB of VRAM. The benchmarks, conducted using a llama.cpp build with Vulkan support, measured performance in tokens per second (tg128) and prompt processing (pp512) across different model sizes and quantization levels. The results indicate varying performance characteristics for each model, with some demonstrating higher throughput than others. AI

IMPACT Provides insights into the real-world performance of various LLMs on consumer-grade hardware, aiding users in hardware selection and model deployment.

RANK_REASON User-generated benchmarks for LLM performance on specific hardware. [lever_c_demoted from research: ic=1 ai=1.0]

Read on r/LocalLLaMA →

• Gemma4
• GTX 1080 Ti
• llama.cpp
• P100s
• Qwen3.6

• infra

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