Laguna XS.2 and M.1
The company has released two new agentic coding models, Laguna M.1 and Laguna XS.2, designed for long-horizon tasks. Laguna M.1 is a 225B-parameter Mixture of Experts model trained in-house, while Laguna XS.2 is a smaller 33B-parameter open-weight model available under Apache 2.0. Both models are accessible via API and OpenRouter for a limited time, with XS.2 marking the company's first open-weight release. The models were developed using proprietary data pipelines, synthetic data, and reinforcement learning infrastructure.
- ▪Laguna M.1 is a 225B total parameter Mixture of Experts model with 23B activated parameters, trained on 30T tokens using 6,144 NVIDIA Hopper GPUs.
- ▪Laguna XS.2 is a 33B-parameter MoE model with 3B activated parameters and achieves 44.5% on SWE-bench Pro and 30.1% on Terminal-Bench 2.0.
- ▪Laguna XS.2 is the company’s first open-weight model, released under the Apache 2.0 license to support the open ecosystem.
- ▪Both models are built for agentic coding and long-horizon tasks, using an in-house agent runtime and reinforcement learning framework.
- ▪The company used synthetic data (about 13% of training mix) and an automated data mixture optimization system called AutoMixer during training.
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2026-04-28 Laguna XS.2 and M.1: A Deeper Dive Poolside team Table of contents We’ve released the first two models in the Laguna family, Laguna M.1 and Laguna XS.2, alongside the runtime we use to train and operate agents, available through two product experiences in preview.Open weightsComing soonWorking with NVIDIAModel buildingData and automixingMuonAgent RLGet started We’ve released the first two models in the Laguna family, Laguna M.1 and Laguna XS.2, alongside the runtime we use to train and operate agents, available through two product experiences in preview.Laguna M.1 came first, finishing pre-training at the end of last year; it's the foundation for everything else we're building across the family.
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