DeepSeek V4 Pro vs Laguna M.1

Pick DeepSeek V4 Pro if you want the stronger benchmark profile. Laguna M.1 only becomes the better choice if you want the cheaper token bill or you want the stronger reasoning-first profile.

DeepSeek V4 Pro is clearly ahead on the provisional aggregate, 71 to 46. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

DeepSeek V4 Pro's sharpest advantage is in agentic, where it averages 59.1 against 40.7. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 59.1% to 40.7%.

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 Laguna M.1. That is roughly Infinityx on output cost alone. Laguna M.1 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 131K for Laguna M.1.