GLM-5V-Turbo vs Qwen3.5 397B (Reasoning)

Pick Qwen3.5 397B (Reasoning) if you want the stronger benchmark profile. GLM-5V-Turbo only becomes the better choice if you need the larger 200K context window or you would rather avoid the extra latency and token burn of a reasoning model.

Qwen3.5 397B (Reasoning) is clearly ahead on the aggregate, 77 to 58. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Qwen3.5 397B (Reasoning)'s sharpest advantage is in agentic, where it averages 74.8 against 58. The single biggest benchmark swing on the page is BrowseComp, 51.9% to 78%.

GLM-5V-Turbo is also the more expensive model on tokens at $1.20 input / $4.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.5 397B (Reasoning). That is roughly Infinityx on output cost alone. Qwen3.5 397B (Reasoning) is the reasoning model in the pair, while GLM-5V-Turbo 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. GLM-5V-Turbo gives you the larger context window at 200K, compared with 128K for Qwen3.5 397B (Reasoning).