AI November 8, 2026 mixed ⇧ 1877 pts across 3 threads

Nobody trusts coding benchmarks anymore

MaxxBench is pitched as a skeptical reply to a DeepSWE score ("Nice DeepSWE score. But is it true?"), and the thread treats it half as a joke and half as a real complaint. One commenter says real programming is full of these small, annoying changes. Another says there is always a huge gap between benchmarks and real-world ability, and calls both deepseek 4.1 flash and haiku 5.5 "fast garbage producers" for their use case.

The same distrust shows up in the local-model threads. People test on their own tasks, like transposing a bit in a scalar function, and in the harness thread, where one person's own nightly runs contradict how the tools are marketed.

The pattern: published scores no longer persuade practitioners, and personal evals are becoming the default way to pick a model.


So what?

If you sell anything model-dependent, a leaderboard number won't win skeptical buyers. Build and publish an eval on real customer tasks. If you pick models yourself, keep a private test set and rerun it whenever a new release lands.

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