Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.2 is clearly ahead on the aggregate, 88 to 58. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.2's sharpest advantage is in coding, where it averages 81.8 against 33.2. The single biggest benchmark swing on the page is LiveCodeBench, 79 to 29.
GPT-5.2 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-5.2 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-5.2 gives you the larger context window at 400K, compared with 128K for Aion-2.0.
Pick GPT-5.2 if you want the stronger benchmark profile. Aion-2.0 only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5.2
85.4
Aion-2.0
51.7
GPT-5.2
81.8
Aion-2.0
33.2
GPT-5.2
95
Aion-2.0
66
GPT-5.2
93.2
Aion-2.0
70.3
GPT-5.2
79.5
Aion-2.0
54
GPT-5.2
94
Aion-2.0
93
GPT-5.2
92.4
Aion-2.0
78.1
GPT-5.2
97.2
Aion-2.0
72.1
GPT-5.2 is ahead overall, 88 to 58. The biggest single separator in this matchup is LiveCodeBench, where the scores are 79 and 29.
GPT-5.2 has the edge for knowledge tasks in this comparison, averaging 79.5 versus 54. Inside this category, HLE is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for coding in this comparison, averaging 81.8 versus 33.2. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for math in this comparison, averaging 97.2 versus 72.1. Inside this category, MATH-500 is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for reasoning in this comparison, averaging 93.2 versus 70.3. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for agentic tasks in this comparison, averaging 85.4 versus 51.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for multimodal and grounded tasks in this comparison, averaging 95 versus 66. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for instruction following in this comparison, averaging 94 versus 93. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for multilingual tasks in this comparison, averaging 92.4 versus 78.1. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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