DeepSeek V4 Pro vs GLM-4.7

Pick DeepSeek V4 Pro if you want the stronger benchmark profile. GLM-4.7 only becomes the better choice if coding is the priority or you want the cheaper token bill.

DeepSeek V4 Pro finishes one point ahead on BenchLM's provisional leaderboard, 71 to 70. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.

DeepSeek V4 Pro's sharpest advantage is in agentic, where it averages 59.1 against 45.3. The single biggest benchmark swing on the page is LiveCodeBench, 56.8% to 84.9%. GLM-4.7 does hit back in coding, so the answer changes if that is the part of the workload you care about most.

DeepSeek V4 Pro is also the more expensive model on tokens at $1.74 input / $3.48 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 DeepSeek V4 Pro 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 Pro gives you the larger context window at 1M, compared with 200K for GLM-4.7.