Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
o1 has the cleaner overall profile here, landing at 68 versus 66. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
o1's sharpest advantage is in knowledge, where it averages 69.6 against 60.8. The single biggest benchmark swing on the page is AIME 2024, 74.3 to 87. Step 3.5 Flash does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.
o1 is also the more expensive model on tokens at $15.00 input / $60.00 output per 1M tokens, versus $0.10 input / $0.30 output per 1M tokens for Step 3.5 Flash. That is roughly 200.0x on output cost alone. o1 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 200K for o1.
Pick o1 if you want the stronger benchmark profile. Step 3.5 Flash only becomes the better choice if mathematics is the priority or you want the cheaper token bill.
o1
65.4
Step 3.5 Flash
60.2
o1
48.4
Step 3.5 Flash
47.1
o1
70.7
Step 3.5 Flash
66.7
o1
78.1
Step 3.5 Flash
78.3
o1
69.6
Step 3.5 Flash
60.8
o1
92.2
Step 3.5 Flash
87
o1
77
Step 3.5 Flash
82.8
o1
74.3
Step 3.5 Flash
84.5
o1 is ahead overall, 68 to 66. The biggest single separator in this matchup is AIME 2024, where the scores are 74.3 and 87.
o1 has the edge for knowledge tasks in this comparison, averaging 69.6 versus 60.8. Inside this category, MMLU is the benchmark that creates the most daylight between them.
o1 has the edge for coding in this comparison, averaging 48.4 versus 47.1. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Step 3.5 Flash has the edge for math in this comparison, averaging 84.5 versus 74.3. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
Step 3.5 Flash has the edge for reasoning in this comparison, averaging 78.3 versus 78.1. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
o1 has the edge for agentic tasks in this comparison, averaging 65.4 versus 60.2. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
o1 has the edge for multimodal and grounded tasks in this comparison, averaging 70.7 versus 66.7. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
o1 has the edge for instruction following in this comparison, averaging 92.2 versus 87. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Step 3.5 Flash has the edge for multilingual tasks in this comparison, averaging 82.8 versus 77. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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