Inference engineering Pareto atlas identifies dominant configurations for cost, quality, and latency across 54 setups on Qwen2.5-7B-Instruct with vLLM, calibrating a Pareto frontier across L4, A100, and H100 GPUs
Read the original at arxiv.org→arXiv:2609.17863v1 Announce Type: new Abstract: LLM inference optimizations report speedups on different models, GPUs, prompts, and quality metrics, making them hard to compare or combine. We build a cost, quality,...
Original headline: "The Inference Engineering Pareto Atlas: Which Optimizations Dominate the Cost, Quality, and Latency Frontier?"
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- Sep 17, 04:00 UTC arXiv cs.AI lead source The Inference Engineering Pareto Atlas: Which Optimizations Dominate the Cost, Quality, and Latency Frontier?