GLM-5 vs Step 3.7 Flash

Pick Step 3.7 Flash if you want the stronger benchmark profile. GLM-5 only becomes the better choice if coding is the priority or you would rather avoid the extra latency and token burn of a reasoning model.

Step 3.7 Flash is clearly ahead on the provisional aggregate, 72 to 67. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Step 3.7 Flash's sharpest advantage is in agentic, where it averages 65.9 against 56.2. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 56.2% to 59.5%. GLM-5 does hit back in coding, 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 $0.20 input / $1.15 output per 1M tokens for Step 3.7 Flash. That is roughly 2.8x on output cost alone. Step 3.7 Flash 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. Step 3.7 Flash gives you the larger context window at 256K, compared with 200K for GLM-5.