Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5 mini is clearly ahead on the aggregate, 69 to 58. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5 mini's sharpest advantage is in multimodal & grounded, where it averages 83.8 against 66. The single biggest benchmark swing on the page is MMMU-Pro, 86 to 61. Aion-2.0 does hit back in instruction following, so the answer changes if that is the part of the workload you care about most.
GPT-5 mini 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.
Pick GPT-5 mini if you want the stronger benchmark profile. Aion-2.0 only becomes the better choice if instruction following is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5 mini
65.7
Aion-2.0
51.7
GPT-5 mini
42.8
Aion-2.0
33.2
GPT-5 mini
83.8
Aion-2.0
66
GPT-5 mini
81.8
Aion-2.0
70.3
GPT-5 mini
62.8
Aion-2.0
54
GPT-5 mini
82
Aion-2.0
93
GPT-5 mini
80.1
Aion-2.0
78.1
GPT-5 mini
87.2
Aion-2.0
72.1
GPT-5 mini is ahead overall, 69 to 58. The biggest single separator in this matchup is MMMU-Pro, where the scores are 86 and 61.
GPT-5 mini has the edge for knowledge tasks in this comparison, averaging 62.8 versus 54. Inside this category, HLE is the benchmark that creates the most daylight between them.
GPT-5 mini has the edge for coding in this comparison, averaging 42.8 versus 33.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
GPT-5 mini has the edge for math in this comparison, averaging 87.2 versus 72.1. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
GPT-5 mini has the edge for reasoning in this comparison, averaging 81.8 versus 70.3. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
GPT-5 mini has the edge for agentic tasks in this comparison, averaging 65.7 versus 51.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5 mini has the edge for multimodal and grounded tasks in this comparison, averaging 83.8 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 82. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5 mini has the edge for multilingual tasks in this comparison, averaging 80.1 versus 78.1. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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