AI model benchmark scores can be significantly affected by the test harness and configuration used, not just the model itself; the same model can show dramatically different scores depending on how it is tested, as demonstrated by a study showing Cursor's ranking jumping from top 30 to top 5 by changing only the harness configuration.
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AI Model Scores Flawed: Harness Affects Results! #shortsAdded:
Two independent sources, different methodologies, same conclusion.
Anthropic's newer model is is worse than the one it replaced.
And a researcher named Bustamante published a study this week proving the benchmark scores change dramatically based on which harness you use, which which thing you add to the model.
Same model, different harness, different score. Cursor jumped from top 30 to top five by changing only the harness configuration.
The model is the same, the score moved because the test setup moved. Nobody else is testing for this. Tab tests 101 harnesses, I'm proud to say.
101 harness configurations because the model isn't the score, like we just said. The model plus the harness plus the configuration equals the score.
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