Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
o3 is clearly ahead on the aggregate, 63 to 57. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o3's sharpest advantage is in agentic, where it averages 69.2 against 57. MiniMax M2.7 does hit back in coding, so the answer changes if that is the part of the workload you care about most.
o3 is also the more expensive model on tokens at $10.00 input / $40.00 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M2.7. That is roughly 33.3x on output cost alone. o3 is the reasoning model in the pair, while MiniMax M2.7 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 o3 if you want the stronger benchmark profile. MiniMax M2.7 only becomes the better choice if coding is the priority or you want the cheaper token bill.
MiniMax M2.7
57
o3
69.2
MiniMax M2.7
56.2
o3
48.3
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
o3 is ahead overall, 63 to 57.
MiniMax M2.7 has the edge for coding in this comparison, averaging 56.2 versus 48.3. o3 stays close enough that the answer can still flip depending on your workload.
o3 has the edge for agentic tasks in this comparison, averaging 69.2 versus 57. MiniMax M2.7 stays close enough that the answer can still flip depending on your workload.
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