DeepSeek V4 Flash (Max) vs GLM-5

Pick DeepSeek V4 Flash (Max) if you want the stronger benchmark profile. GLM-5 only becomes the better choice if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model.

DeepSeek V4 Flash (Max) is clearly ahead on the provisional aggregate, 77 to 67. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

DeepSeek V4 Flash (Max)'s sharpest advantage is in coding, where it averages 73.7 against 63.2. The single biggest benchmark swing on the page is HLE, 34.8% to 50.4%. GLM-5 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.

GLM-5 is also the more expensive model on tokens at $1.00 input / $3.20 output per 1M tokens, versus $0.14 input / $0.28 output per 1M tokens for DeepSeek V4 Flash (Max). That is roughly 11.4x on output cost alone. DeepSeek V4 Flash (Max) is the reasoning model in the pair, while GLM-5 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. DeepSeek V4 Flash (Max) gives you the larger context window at 1M, compared with 200K for GLM-5.