Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Aion-2.0 is clearly ahead on the aggregate, 58 to 49. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Aion-2.0's sharpest advantage is in mathematics, where it averages 72.1 against 9.8. The single biggest benchmark swing on the page is AIME 2024, 76 to 9.8. GPT-4.1 nano does hit back in reasoning, so the answer changes if that is the part of the workload you care about most.
Aion-2.0 is also the more expensive model on tokens at $0.80 input / $1.60 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for GPT-4.1 nano. That is roughly 4.0x on output cost alone. GPT-4.1 nano gives you the larger context window at 1M, compared with 128K for Aion-2.0.
Pick Aion-2.0 if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if reasoning is the priority or you want the cheaper token bill.
Aion-2.0
51.7
GPT-4.1 nano
47.4
Aion-2.0
33.2
GPT-4.1 nano
18
Aion-2.0
66
GPT-4.1 nano
59.3
Aion-2.0
70.3
GPT-4.1 nano
74.1
Aion-2.0
54
GPT-4.1 nano
50.7
Aion-2.0
93
GPT-4.1 nano
83.2
Aion-2.0
78.1
GPT-4.1 nano
59
Aion-2.0
72.1
GPT-4.1 nano
9.8
Aion-2.0 is ahead overall, 58 to 49. The biggest single separator in this matchup is AIME 2024, where the scores are 76 and 9.8.
Aion-2.0 has the edge for knowledge tasks in this comparison, averaging 54 versus 50.7. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Aion-2.0 has the edge for coding in this comparison, averaging 33.2 versus 18. Inside this category, SWE-bench Pro 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 9.8. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
GPT-4.1 nano has the edge for reasoning in this comparison, averaging 74.1 versus 70.3. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
Aion-2.0 has the edge for agentic tasks in this comparison, averaging 51.7 versus 47.4. Inside this category, OSWorld-Verified is the benchmark that creates the most daylight between them.
Aion-2.0 has the edge for multimodal and grounded tasks in this comparison, averaging 66 versus 59.3. 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 83.2. 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 59. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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