Kimi K2.6 vs MiniMax M2.7

Pick Kimi K2.6 if you want the stronger benchmark profile. MiniMax M2.7 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.

Kimi K2.6 is clearly ahead on the provisional aggregate, 84 to 62. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Kimi K2.6's sharpest advantage is in coding, where it averages 72 against 53.7. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 66.7% to 57%.

Kimi K2.6 is also the more expensive model on tokens at $0.95 input / $4.00 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M2.7. That is roughly 3.3x on output cost alone. Kimi K2.6 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. Kimi K2.6 gives you the larger context window at 256K, compared with 200K for MiniMax M2.7.