Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-4.1 is clearly ahead on the aggregate, 65 to 58. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-4.1's sharpest advantage is in coding, where it averages 51.7 against 33.2. The single biggest benchmark swing on the page is AIME 2024, 26.4 to 76. Aion-2.0 does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.
GPT-4.1 is also the more expensive model on tokens at $2.00 input / $8.00 output per 1M tokens, versus $0.80 input / $1.60 output per 1M tokens for Aion-2.0. That is roughly 5.0x on output cost alone. GPT-4.1 gives you the larger context window at 1M, compared with 128K for Aion-2.0.
Pick GPT-4.1 if you want the stronger benchmark profile. Aion-2.0 only becomes the better choice if mathematics is the priority or you want the cheaper token bill.
GPT-4.1
64.7
Aion-2.0
51.7
GPT-4.1
51.7
Aion-2.0
33.2
GPT-4.1
73.6
Aion-2.0
66
GPT-4.1
80.9
Aion-2.0
70.3
GPT-4.1
63.3
Aion-2.0
54
GPT-4.1
87.4
Aion-2.0
93
GPT-4.1
69
Aion-2.0
78.1
GPT-4.1
26.4
Aion-2.0
72.1
GPT-4.1 is ahead overall, 65 to 58. The biggest single separator in this matchup is AIME 2024, where the scores are 26.4 and 76.
GPT-4.1 has the edge for knowledge tasks in this comparison, averaging 63.3 versus 54. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-4.1 has the edge for coding in this comparison, averaging 51.7 versus 33.2. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Aion-2.0 has the edge for math in this comparison, averaging 72.1 versus 26.4. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
GPT-4.1 has the edge for reasoning in this comparison, averaging 80.9 versus 70.3. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
GPT-4.1 has the edge for agentic tasks in this comparison, averaging 64.7 versus 51.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-4.1 has the edge for multimodal and grounded tasks in this comparison, averaging 73.6 versus 66. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Aion-2.0 has the edge for instruction following in this comparison, averaging 93 versus 87.4. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Aion-2.0 has the edge for multilingual tasks in this comparison, averaging 78.1 versus 69. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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