Hemingway Bench in this channel In the captured material, the Hemingway Bench comes up in the conversation with Edwin Chen, founder of Surge AI, as one of the novel mathematics and writing benchmarks he points to when weighing what current model evaluations actually reveal — and what their incentives get wrong [^164099f4-1fa6-5fd7-9b78-a9844ece7836]. It sits alongside research-level benchmarks like Erdős-style refutations in the same part of the discussion, as evidence of where model progress can be measured and where benchmark design can mislead. Why it matters Benchmarks like this matter because they shape what model builders optimize for. In the video's framing, exploring these newer writing and math benchmarks is a way to understand both genuine progress and the misaligned incentives that benchmarks can create. - The Hemingway Bench appears as an example of a novel writing benchmark in the Edwin Chen conversation. - It is discussed in the same breath as research-level math benchmarks (Erdős-style refutations). - Its role in the discussion is to probe both model progress and the misaligned incentives benchmarks can introduce.