The Sequence AI of the Week #903: Laguna, the 118 Billion Parameters that Walks Into a Trillion-Parameter Bar
TheSequence Jesus Rodriguez ● Covered by 3 sources
Poolside AI released Laguna, a 118 billion-parameter open-weight model that substantially outperforms much larger models on multiple benchmarks, scoring 70.2% on Terminal-Bench 2.1 compared to 64.0% for DeepSeek-V4-Pro-Max at 1.6 trillion parameters. On the harder DeepSWE benchmark, Laguna achieves 40.4 versus DeepSeek-V4-Pro-Max's 9.0, showing a 4x score advantage despite using 13 times fewer parameters. The result challenges expectations that model performance scales primarily with parameter count and suggests architectural or training innovations enable competitive performance at smaller scale.
Why it matters
Poolside’s 118B coding model beats systems ten times its size. The interesting part is not the architecture.
