GLM-5V-Turbo vs GPT-5.4 nano

Treat this as a split decision. GLM-5V-Turbo makes more sense if agentic is the priority or you would rather avoid the extra latency and token burn of a reasoning model; GPT-5.4 nano is the better fit if you want the cheaper token bill or you need the larger 400K context window.

GLM-5V-Turbo and GPT-5.4 nano finish on the same overall score, so this is less about a single winner and more about where the edge shows up. The headline says tie; the benchmark table is where the real choice happens.

GLM-5V-Turbo is also the more expensive model on tokens at $1.20 input / $4.00 output per 1M tokens, versus $0.20 input / $1.25 output per 1M tokens for GPT-5.4 nano. That is roughly 3.2x on output cost alone. GPT-5.4 nano 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. GPT-5.4 nano gives you the larger context window at 400K, compared with 200K for GLM-5V-Turbo.