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 45. 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 multilingual, where it averages 78.1 against 48. The single biggest benchmark swing on the page is MMLU-ProX, 77 to 48. GPT-5 nano does hit back in mathematics, 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 $0.05 input / $0.40 output per 1M tokens for GPT-5 nano. That is roughly 4.0x on output cost alone. GPT-5 nano is the reasoning model in the pair, while Aion-2.0 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 nano gives you the larger context window at 400K, compared with 128K for Aion-2.0.
Pick Aion-2.0 if you want the stronger benchmark profile. GPT-5 nano only becomes the better choice if mathematics is the priority or you want the cheaper token bill.
Aion-2.0
51.7
GPT-5 nano
37.7
Aion-2.0
33.2
GPT-5 nano
22
Aion-2.0
66
GPT-5 nano
56.7
Aion-2.0
70.3
GPT-5 nano
58.8
Aion-2.0
54
GPT-5 nano
63.7
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Aion-2.0
78.1
GPT-5 nano
48
Aion-2.0
72.1
GPT-5 nano
85.2
Aion-2.0 is ahead overall, 58 to 45. The biggest single separator in this matchup is MMLU-ProX, where the scores are 77 and 48.
GPT-5 nano has the edge for knowledge tasks in this comparison, averaging 63.7 versus 54. Inside this category, FrontierScience 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 22. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
GPT-5 nano has the edge for math in this comparison, averaging 85.2 versus 72.1. Inside this category, AIME 2025 is the benchmark that creates the most daylight between them.
Aion-2.0 has the edge for reasoning in this comparison, averaging 70.3 versus 58.8. 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 37.7. 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 56.7. Inside this category, OfficeQA Pro 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 48. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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