While working on a business website i needed to figure out which model actually handles complex coding stuff better. So i ran some spatial reasoning tests on chatgpt o4 and claude opus 4.5 to see how they deal with messy legacy code and refactoring.
Basically fed both models some old code with tons of nested dependencies, asked them to refactor, identify bugs, suggest better architecture. Did this over 15 different scenarios and tracked accuracy, context handling, token usage to get a real picture..
On 500+ line files, claude was hitting ~85% accurate bug detection while chatgpt o4 was around 72%. Refactoring quality had a bigger gap - claude gave usable results ~78% of the time vs chatgpt's 65%.
the thing that really stood out was context retention. Claude handled 8-10 files no problem, chatgpt started losing track after 5-6 especially with heavy cross-references.
Token efficiency went to claude too, ~120k tokens per full run vs chatgpt's 180k for the same task. Claude's just noticeably better at the spatial reasoning side of code architecture, chatgpt loses dependency chains quicker when everything references everything else.
While digging around i came across qwen3 coder 480b on deepinfra - apparently solid benchmarks for agentic coding tasks and performance pretty comparable to claude. Keeping it on the list to try later, but we're already hooked up with claude and it's working good enough right now.
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