GLM-4.7 vs Ling 2.6 Flash

Pick GLM-4.7 if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if you need the larger 262K context window or you would rather avoid the extra latency and token burn of a reasoning model.

GLM-4.7 is clearly ahead on the provisional aggregate, 71 to 44. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

GLM-4.7's sharpest advantage is in coding, where it averages 70.6 against 27. The single biggest benchmark swing on the page is GPQA, 85.7% to 59%.

Ling 2.6 Flash is also the more expensive model on tokens at $0.10 input / $0.30 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for GLM-4.7. That is roughly Infinityx on output cost alone. GLM-4.7 is the reasoning model in the pair, while Ling 2.6 Flash 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. Ling 2.6 Flash gives you the larger context window at 262K, compared with 200K for GLM-4.7.