Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.2 Pro is clearly ahead on the aggregate, 90 to 66. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.2 Pro's sharpest advantage is in coding, where it averages 84.8 against 47.1. The single biggest benchmark swing on the page is SWE-bench Pro, 89 to 49.
GPT-5.2 Pro is also the more expensive model on tokens at $25.00 input / $150.00 output per 1M tokens, versus $0.10 input / $0.30 output per 1M tokens for Step 3.5 Flash. That is roughly 500.0x on output cost alone. GPT-5.2 Pro 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. GPT-5.2 Pro gives you the larger context window at 400K, compared with 256K for Step 3.5 Flash.
Pick GPT-5.2 Pro if you want the stronger benchmark profile. Step 3.5 Flash only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5.2 Pro
85.9
Step 3.5 Flash
60.2
GPT-5.2 Pro
84.8
Step 3.5 Flash
47.1
GPT-5.2 Pro
96
Step 3.5 Flash
66.7
GPT-5.2 Pro
95.2
Step 3.5 Flash
78.3
GPT-5.2 Pro
81.5
Step 3.5 Flash
60.8
GPT-5.2 Pro
95
Step 3.5 Flash
87
GPT-5.2 Pro
93.4
Step 3.5 Flash
82.8
GPT-5.2 Pro
98.2
Step 3.5 Flash
84.5
GPT-5.2 Pro is ahead overall, 90 to 66. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 89 and 49.
GPT-5.2 Pro has the edge for knowledge tasks in this comparison, averaging 81.5 versus 60.8. Inside this category, HLE is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for coding in this comparison, averaging 84.8 versus 47.1. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for math in this comparison, averaging 98.2 versus 84.5. Inside this category, HMMT Feb 2023 is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for reasoning in this comparison, averaging 95.2 versus 78.3. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for agentic tasks in this comparison, averaging 85.9 versus 60.2. Inside this category, OSWorld-Verified is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 96 versus 66.7. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for instruction following in this comparison, averaging 95 versus 87. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for multilingual tasks in this comparison, averaging 93.4 versus 82.8. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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