Poolside just released Laguna S 2.1, a 118B MoE coding model that activates only 8B parameters per token alongside a 1M token context window. Built in under nine weeks, its thinking mode boosts DeepSWE benchmark scores from 16.5% to 40.4%, matching or beating models many times its size. Weights and full evaluation trajectories are already available for download.
Poolside just launched its first public coding models, headlined by Laguna XS.2, an open-weights 33B model (3B active) under Apache 2.0 that runs on a single GPU. The lab also unveiled Laguna M.1, a massive 225B MoE, alongside preview tools pool (a terminal agent) and Shimmer (a cloud sandbox). Both models are temporarily free via API and OpenRouter, bringing serious agentic horsepower to local setups.
EleutherAI just released The Common Pile v0.1, an 8-terabyte AI training dataset built entirely from licensed and public domain text over two years. Alongside it, the team dropped two 7B Comma models that perform on par with early Llama models, pushing back on the industry narrative that frontier AI requires unpermitted scraping.
