Laguna M.1 vs Qwen3.5 397B

Pick Qwen3.5 397B if you want the stronger benchmark profile. Laguna M.1 only becomes the better choice if you want the cheaper token bill or you need the larger 131K context window.

Qwen3.5 397B is clearly ahead on the provisional aggregate, 64 to 46. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Qwen3.5 397B's sharpest advantage is in agentic, where it averages 56.2 against 40.7. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 40.7% to 52.5%.

Qwen3.5 397B is also the more expensive model on tokens at $0.60 input / $3.60 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 Qwen3.5 397B 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. Laguna M.1 gives you the larger context window at 131K, compared with 128K for Qwen3.5 397B.