Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
o1 is clearly ahead on the aggregate, 68 to 58. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o1's sharpest advantage is in knowledge, where it averages 69.6 against 54. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 66 to 48. Aion-2.0 does hit back in multilingual, so the answer changes if that is the part of the workload you care about most.
o1 is also the more expensive model on tokens at $15.00 input / $60.00 output per 1M tokens, versus $0.80 input / $1.60 output per 1M tokens for Aion-2.0. That is roughly 37.5x on output cost alone. o1 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. o1 gives you the larger context window at 200K, compared with 128K for Aion-2.0.
Pick o1 if you want the stronger benchmark profile. Aion-2.0 only becomes the better choice if multilingual is the priority or you want the cheaper token bill.
o1
65.4
Aion-2.0
51.7
o1
48.4
Aion-2.0
33.2
o1
70.7
Aion-2.0
66
o1
78.1
Aion-2.0
70.3
o1
69.6
Aion-2.0
54
o1
92.2
Aion-2.0
93
o1
77
Aion-2.0
78.1
o1
74.3
Aion-2.0
72.1
o1 is ahead overall, 68 to 58. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 66 and 48.
o1 has the edge for knowledge tasks in this comparison, averaging 69.6 versus 54. Inside this category, MMLU is the benchmark that creates the most daylight between them.
o1 has the edge for coding in this comparison, averaging 48.4 versus 33.2. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
o1 has the edge for math in this comparison, averaging 74.3 versus 72.1. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
o1 has the edge for reasoning in this comparison, averaging 78.1 versus 70.3. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
o1 has the edge for agentic tasks in this comparison, averaging 65.4 versus 51.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
o1 has the edge for multimodal and grounded tasks in this comparison, averaging 70.7 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 92.2. 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 77. o1 stays close enough that the answer can still flip depending on your workload.
Get notified when new models drop, benchmark scores change, or the leaderboard shifts. One email per week.
Free. No spam. Unsubscribe anytime. We only store derived location metadata for consent routing.