Today we’re releasing Poolside Laguna S 2.1
It is a 118B-total, 8B-active open-weight model built for agentic coding and long-horizon work, with context up to 1M tokens
https://t.co/Q9tkk2al4g
Laguna S 2.1 sits at the top of its weight class and competes with open models many times larger, while remaining small enough to run on a single NVIDIA DGX Spark
It is available today under OpenMDW-1.1 via Hugging Face, OpenRouter, the Poolside API, and pool
This is a remarkable model by any measure. As much as we can gather, it's the best open weight model in the West, regardless of size
But the model itself is only part of the story
There is a prevailing narrative that building capable models requires ever more capital, compute, and people. We believe the more important question is how efficiently you can turn those resources into intelligence
At Poolside, we approach model building as an industrialized process spanning data, pre-training, reinforcement learning, evaluation, and inference. We call that system the Model Factory. We have written about our approach to model building extensively in a 6 part blog series: https://t.co/RL7PG2fcdH
Laguna S 2.1 went from the Model Factory kicking it off to release in 52 days. The model is the output. The ability to keep building better models, faster and more efficiently each time is the actual innovation. The Model Factory is Poolside's compounding asset
And so here we are, 52 days after kicking this off, releasing a 118B/8B MOE that tops 70% on TB 2.1, 78% on SWE-Bench Multi, 59% on SWE-Bench Pro, and 40% on DeepSWE. And it's fully open, from an American company
I grew up in the Linux and Python communities, then spent much of my career at Canonical (Ubuntu), Heroku and GitHub. Those communities shaped my belief that important technology becomes more useful when people can understand it, challenge it, and build upon it. And even more important than being useful is being trusted.
That is what open weights mean to me. They are not a marketing or distribution exercise. They give people control: the ability to inspect the work, reproduce the claims, modify the model, and run it inside their own environment
I believe the West needs a credible open path to frontier intelligence. I believe it should be from an American company. We intend to be that company
Laguna S 2.1 is another step in that direction and yet more evidence of Poolside's long held, often times contrarian beliefs and views on how intelligence will be built.
One last note. We are doing something very different that we hope becomes industry norm going forward. We recognize that releasing a 118B/8B MOE that performs as well as Laguna S does would be met with some degree of skepticism. Models of this size are not supposed to outperform models 4-25x larger. We double and triple checked our benchmark trajectories to be sure. But we wanted to go another step and release those trajectories for you to see and help us quadruple check them.
https://t.co/KkleqWVwb9
If you find something we missed, we genuinely want to hear about
Have fun building whatever thing you can think of with the most persistent little model that could
