DeepSeek V4 Pro (Max) vs MiniMax M3

Pick DeepSeek V4 Pro (Max) if you want the stronger benchmark profile. MiniMax M3 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.

DeepSeek V4 Pro (Max) is clearly ahead on the provisional aggregate, 87 to 76. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

DeepSeek V4 Pro (Max)'s sharpest advantage is in coding, where it averages 75.9 against 67. The single biggest benchmark swing on the page is SWE-bench Pro, 55.4% to 59%.

DeepSeek V4 Pro (Max) is also the more expensive model on tokens at $1.74 input / $3.48 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M3. That is roughly 2.9x on output cost alone. DeepSeek V4 Pro (Max) is the reasoning model in the pair, while MiniMax M3 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.