Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemini 2.5 Pro is clearly ahead on the aggregate, 67 to 58. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemini 2.5 Pro's sharpest advantage is in multimodal & grounded, where it averages 85.1 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.
Gemini 2.5 Pro is also the more expensive model on tokens at $1.25 input / $5.00 output per 1M tokens, versus $0.80 input / $1.60 output per 1M tokens for Aion-2.0. That is roughly 3.1x on output cost alone. Gemini 2.5 Pro gives you the larger context window at 1M, compared with 128K for Aion-2.0.
Pick Gemini 2.5 Pro if you want the stronger benchmark profile. Aion-2.0 only becomes the better choice if instruction following is the priority or you want the cheaper token bill.
Gemini 2.5 Pro
61.7
Aion-2.0
51.7
Gemini 2.5 Pro
41
Aion-2.0
33.2
Gemini 2.5 Pro
85.1
Aion-2.0
66
Gemini 2.5 Pro
80.7
Aion-2.0
70.3
Gemini 2.5 Pro
58.4
Aion-2.0
54
Gemini 2.5 Pro
83
Aion-2.0
93
Gemini 2.5 Pro
82.7
Aion-2.0
78.1
Gemini 2.5 Pro
83.5
Aion-2.0
72.1
Gemini 2.5 Pro is ahead overall, 67 to 58. The biggest single separator in this matchup is MMMU-Pro, where the scores are 86 and 61.
Gemini 2.5 Pro has the edge for knowledge tasks in this comparison, averaging 58.4 versus 54. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Gemini 2.5 Pro has the edge for coding in this comparison, averaging 41 versus 33.2. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Gemini 2.5 Pro has the edge for math in this comparison, averaging 83.5 versus 72.1. Inside this category, MATH-500 is the benchmark that creates the most daylight between them.
Gemini 2.5 Pro has the edge for reasoning in this comparison, averaging 80.7 versus 70.3. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
Gemini 2.5 Pro has the edge for agentic tasks in this comparison, averaging 61.7 versus 51.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Gemini 2.5 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 85.1 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 83. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Gemini 2.5 Pro has the edge for multilingual tasks in this comparison, averaging 82.7 versus 78.1. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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