DeepSeek V3 vs MiMo-V2.5-Pro

Pick MiMo-V2.5-Pro if you want the stronger benchmark profile. DeepSeek V3 only becomes the better choice if knowledge is the priority or you want the cheaper token bill.

MiMo-V2.5-Pro is clearly ahead on the provisional aggregate, 82 to 37. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

MiMo-V2.5-Pro's sharpest advantage is in coding, where it averages 57.2 against 39.2. DeepSeek V3 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.

MiMo-V2.5-Pro is also the more expensive model on tokens at $1.00 input / $3.00 output per 1M tokens, versus $0.27 input / $1.10 output per 1M tokens for DeepSeek V3. That is roughly 2.7x on output cost alone. MiMo-V2.5-Pro is the reasoning model in the pair, while DeepSeek V3 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. MiMo-V2.5-Pro gives you the larger context window at 1M, compared with 128K for DeepSeek V3.