TL;DRPoolside released Laguna S 2.1, a 118B open-weight coding model that matches larger rivals and runs on a desktop, pitched as the West’s answer to Chinese AI.
Poolside has released Laguna S 2.1, a 118-billion-parameter open-weight model built for agentic coding that the San Francisco startup says matches or exceeds models several times its size. The model uses a mixture-of-experts architecture with eight billion active parameters per token, is compact enough to run on a single Nvidia DGX Spark desktop system, and the weights are available on Hugging Face under the Linux Foundation’s OpenMDW license.
On Terminal-Bench and SWE-Bench Pro, two agentic coding evaluations, Laguna S 2.1 scored just over 70 percent and nearly 60 percent respectively, matching or beating models from DeepSeek, Nvidia, and Thinking Machines that carry two to eight times as many active parameters. Poolside acknowledges the model is “not yet at the frontier,” with closed-source systems from OpenAI and Anthropic still scoring well above it on the same benchmarks.
The release is framed as a direct response to the dominance of Chinese labs in the open-weight category, where DeepSeek, Alibaba’s Qwen family, and Moonshot’s Kimi have set the pace for more than a year. No Western lab had released an open-weight model in the 118-billion-parameter class for 11 months before this launch, according to the company. Forbes reported that Poolside explicitly positioned the release as an effort to give Western enterprises and governments a self-hosted alternative they can run without sending data to a foreign provider.
