{"by":"lasu","descendants":19,"id":50077619,"kids":[50078803,50081136,50085977,50081658,50082128,50081234,50098645,50087383,50082101,50082621,50082228],"score":77,"text":"Existing benchmarks measure solve rate and token output&#x2F;cost, but don&#x27;t punish excess code, which makes a codebase harder to work with in the long term. I wanted to measure this since it matters most for long-term projects.<p>Method: it takes the patches that benchmarks already publish (DeepSWE, SWE-bench Verified, SWE-bench Live) and counts &quot;coding units&quot;: syntax elements like statements, calls, names and literals. I didn&#x27;t use lines of code, so cramming code isn&#x27;t rewarded. Deleted code is subtracted, so it measures net units.<p>GPT-6 and Claude 5.5 have no public patches yet, so I ran them myself on 3–10 tasks on my own subscriptions (shown as faded circles, not ranked).<p>Any feedback or model contributions are welcome, especially public patch exports for newer models.<p>GitHub: <a href=\"https:&#x2F;&#x2F;github.com&#x2F;La5u&#x2F;Parsimony\" rel=\"nofollow\">https:&#x2F;&#x2F;github.com&#x2F;La5u&#x2F;Parsimony</a><p>Not affiliated with any of the benchmarks.","time":1791921031,"title":"Show HN: Parsimony – an open-source benchmark for how much code AI models add","type":"story","url":"https://parsimony.lasu.dev/"}