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arXiv — cs.AI

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The Inference Engineering Pareto Atlas: Which Optimizations Dominate the Cost, Quality, and Latency Frontier?

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, and latency Pareto atlas to identify the best configurations for different deployment constraints. Since…

arXiv — cs.AIBy: Srikanta Datta Tumkur, Jay Iyer, Mehar Simhadri, Sai Pavan Kumar, Sai Kapil Kumar, Ramesh NampellySeptember 17, 2026 (Sep 17)
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AI Summary & Key Takeaways

  • 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, and latency Pareto atlas to identify the best configurations for different deployment constraints
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The Inference Engineering Pareto Atlas: Which Optimizations Dominate the Cost, Quality, and Latency Frontier?

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