GLM-5.2 vs MiniMax M3

Pick GLM-5.2 if you want the stronger benchmark profile. MiniMax M3 only becomes the better choice if coding is the priority or you want the cheaper token bill.

GLM-5.2 is clearly ahead on the provisional aggregate, 94 to 79. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

GLM-5.2's sharpest advantage is in agentic, where it averages 81 against 71.9. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 81% to 66%. MiniMax M3 does hit back in coding, so the answer changes if that is the part of the workload you care about most.

GLM-5.2 is also the more expensive model on tokens at $1.40 input / $4.40 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M3. That is roughly 3.7x on output cost alone. GLM-5.2 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.