Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5 (medium) is clearly ahead on the aggregate, 78 to 66. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5 (medium)'s sharpest advantage is in multimodal & grounded, where it averages 88.1 against 66.7. The single biggest benchmark swing on the page is MMMU-Pro, 89 to 64.
GPT-5 (medium) is the reasoning model in the pair, while Step 3.5 Flash is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Step 3.5 Flash gives you the larger context window at 256K, compared with 128K for GPT-5 (medium).
Pick GPT-5 (medium) if you want the stronger benchmark profile. Step 3.5 Flash only becomes the better choice if you need the larger 256K context window or you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5 (medium)
75.5
Step 3.5 Flash
60.2
GPT-5 (medium)
66.1
Step 3.5 Flash
47.1
GPT-5 (medium)
88.1
Step 3.5 Flash
66.7
GPT-5 (medium)
84.3
Step 3.5 Flash
78.3
GPT-5 (medium)
69.8
Step 3.5 Flash
60.8
GPT-5 (medium)
88
Step 3.5 Flash
87
GPT-5 (medium)
88.1
Step 3.5 Flash
82.8
GPT-5 (medium)
92
Step 3.5 Flash
84.5
GPT-5 (medium) is ahead overall, 78 to 66. The biggest single separator in this matchup is MMMU-Pro, where the scores are 89 and 64.
GPT-5 (medium) has the edge for knowledge tasks in this comparison, averaging 69.8 versus 60.8. Inside this category, HLE is the benchmark that creates the most daylight between them.
GPT-5 (medium) has the edge for coding in this comparison, averaging 66.1 versus 47.1. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
GPT-5 (medium) has the edge for math in this comparison, averaging 92 versus 84.5. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
GPT-5 (medium) has the edge for reasoning in this comparison, averaging 84.3 versus 78.3. Inside this category, BBH is the benchmark that creates the most daylight between them.
GPT-5 (medium) has the edge for agentic tasks in this comparison, averaging 75.5 versus 60.2. Inside this category, OSWorld-Verified is the benchmark that creates the most daylight between them.
GPT-5 (medium) has the edge for multimodal and grounded tasks in this comparison, averaging 88.1 versus 66.7. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-5 (medium) has the edge for instruction following in this comparison, averaging 88 versus 87. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5 (medium) has the edge for multilingual tasks in this comparison, averaging 88.1 versus 82.8. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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