What does it mean when Fable 5 is 1st place and Opus 5 is 3rd place, while Claude code is 7th place? Which model and effort is used for Claude in 7th place, compared to 1st and 3rd?
They are all different problems for the different languages. I was hoping this was a benchmark that attempted to see which languages were more efficient to use with which models.
Exactly. I was wondering what language would be better for heavy agentic workflow. Due to a recent blog post, Clojure seem to be the most terse [1]. But some people are suggesting static types would help in this workflow.
I've had much better experiences with the "budget" tier models than this test suggests I should. I rarely even consider the higher models due to price/use. Perhaps I'm just more vigilant about spec'ing my prompts out before submitting them? Am I just doing too pleb of work? I'm not trying to write custom cuda kernels or hardware integration.
> Potential data contamination: The SWE-bench dataset, comprising a collection of GitHub issues, has been publicly available since the end of 2023. As a result, models released after this date may have seen these exact issues or highly similar data during training. This raises the risk of inflated performance metrics and makes it harder to distinguish genuine generalization from memorization.
[1] : https://martinalderson.com/posts/which-programming-languages...
Edit: In DeepSWE Sol High scores the same as Fable High for ~1/3 of the cost.
> Potential data contamination: The SWE-bench dataset, comprising a collection of GitHub issues, has been publicly available since the end of 2023. As a result, models released after this date may have seen these exact issues or highly similar data during training. This raises the risk of inflated performance metrics and makes it harder to distinguish genuine generalization from memorization.