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ΦBench: Frontier LLM Infrastructure Benchmark

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About ΦBench: Frontier LLM Infrastructure Benchmark

ΦBench is a benchmark suite designed to evaluate whether frontier large language models can engineer the infrastructure that supports them. It comprises 85 tasks spread across nine topics, including GPU kernels, training, inference, serving, and optimization, organized into three escalating task formats. The benchmark provides a leaderboard comparing LLM performance using a scoring system weighted across task categories, with results generated through agent harnesses such as Codex and Claude Code. It also includes an iteration explorer that tracks how models refine their solutions across multiple rounds, presenting observations on exploration strategies and outcome patterns.