Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Step 3.5 Flash is clearly ahead on the aggregate, 66 to 49. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Step 3.5 Flash's sharpest advantage is in mathematics, where it averages 84.5 against 9.8. The single biggest benchmark swing on the page is AIME 2024, 87 to 9.8.
GPT-4.1 nano is also the more expensive model on tokens at $0.10 input / $0.40 output per 1M tokens, versus $0.10 input / $0.30 output per 1M tokens for Step 3.5 Flash. GPT-4.1 nano gives you the larger context window at 1M, compared with 256K for Step 3.5 Flash.
Pick Step 3.5 Flash if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if you need the larger 1M context window.
Step 3.5 Flash
60.2
GPT-4.1 nano
47.4
Step 3.5 Flash
47.1
GPT-4.1 nano
18
Step 3.5 Flash
66.7
GPT-4.1 nano
59.3
Step 3.5 Flash
78.3
GPT-4.1 nano
74.1
Step 3.5 Flash
60.8
GPT-4.1 nano
50.7
Step 3.5 Flash
87
GPT-4.1 nano
83.2
Step 3.5 Flash
82.8
GPT-4.1 nano
59
Step 3.5 Flash
84.5
GPT-4.1 nano
9.8
Step 3.5 Flash is ahead overall, 66 to 49. The biggest single separator in this matchup is AIME 2024, where the scores are 87 and 9.8.
Step 3.5 Flash has the edge for knowledge tasks in this comparison, averaging 60.8 versus 50.7. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Step 3.5 Flash has the edge for coding in this comparison, averaging 47.1 versus 18. Inside this category, SWE-bench Pro 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 9.8. 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 74.1. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
Step 3.5 Flash has the edge for agentic tasks in this comparison, averaging 60.2 versus 47.4. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Step 3.5 Flash has the edge for multimodal and grounded tasks in this comparison, averaging 66.7 versus 59.3. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Step 3.5 Flash has the edge for instruction following in this comparison, averaging 87 versus 83.2. 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 59. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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