DeepSeek V4 Flash vs Laguna M.1

Pick DeepSeek V4 Flash if you want the stronger benchmark profile. Laguna M.1 only becomes the better choice if coding is the priority or you want the cheaper token bill.

DeepSeek V4 Flash is clearly ahead on the provisional aggregate, 57 to 51. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

DeepSeek V4 Flash's sharpest advantage is in agentic, where it averages 49.1 against 45.8. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 49.1% to 45.8%. Laguna M.1 does hit back in coding, so the answer changes if that is the part of the workload you care about most.

DeepSeek V4 Flash is also the more expensive model on tokens at $0.14 input / $0.28 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 Flash 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 Flash gives you the larger context window at 1M, compared with 131K for Laguna M.1.