Introducing Laguna S 2.1
TLDR Dev ● Covered by 2 sources
Poolside AI released Laguna S 2.1, a 118-billion-parameter mixture-of-experts model designed for long-horizon coding tasks and agent work. The model achieved 70.2% on Terminal-Bench 2.1 and 40.4% on DeepSWE v1.1, performing competitively against much larger models while requiring only 8 billion activated parameters per token and training in under nine weeks. The compact model enables complex agentic coding work to run on local machines, with the company publishing full evaluation trajectories to enable transparency about model behavior.
Why it matters
Laguna S 2.1 is a new 118B parameter MoE model designed for effective reasoning and long-horizon tasks with impressive coding performance, improving persistence and verification in problem-solving during training and evaluation.
