Poolside, an AI lab, has released its most capable model, Laguna S 2.1, challenging industry norms with radical transparency. This 118-billion-parameter Mixture-of-Experts model activates only 8 billion parameters per token and supports a massive 1 million token context window. Benchmarks indicate it performs competitively on coding tasks, surpassing larger open models. Poolside made the model weights immediately available on Hugging Face under a permissive license. The rapid nine-week development cycle from pre-training to launch highlights Poolside's accelerated iteration speed. This release addresses a growing demand for trustworthy Western open-weight AI systems. Poolside aims to compete by focusing on cost-effectiveness, self-hosting, and iteration speed rather than raw scale. The model's sparse architecture significantly reduces inference costs, making it economically viable for extensive agentic workloads. Poolside also published complete, unedited benchmark trajectories to enhance credibility and address AI benchmarking issues. Laguna S 2.1 represents the most credible Western open-weight option for self-hosted agentic coding in nearly a year.