Poolside releases Laguna S 2.1, an open-weight coding model that beats rivals 10x its size
Poolside, a San Francisco AI lab that has spent most of its three-year existence selling coding models to governments and defense agencies, released Laguna S 2.1 on Tuesday, July 21, 2026. The 118-billion-parameter Mixture-of-Experts (MoE) model activates only 8 billion parameters per token and supports a context window of up to 1 million tokens. Weights went live immediately on Hugging Face under the permissive OpenMDW-1.1 license.
What is Laguna S 2.1?
Laguna S 2.1 is an open-weight coding model from Poolside built around a sparse MoE architecture. The model uses 256 routed experts plus one shared expert, grouped-query attention, and interleaved sliding-window layers. Because inference cost scales with the 8 billion active parameters rather than the full 118 billion, Poolside says the model is small enough to run on a single Nvidia DGX Spark.
How does it perform on coding benchmarks?
On Terminal-Bench 2.1, which measures long-horizon terminal tasks, Laguna S 2.1 scores 70.2 percent, placing 11th on the company’s compiled leaderboard. It runs ahead of DeepSeek-V4-Pro-Max, a 1.6-trillion-parameter model that scored 64.0, Thinking Machines Inkling at 975 billion parameters and 63.8, and Nvidia Nemotron 3 Ultra at 550 billion parameters and 56.4.
On SWE-Bench Multilingual, Laguna S 2.1 posts 78.5 percent, and on the SWE-Bench Pro public dataset it reaches 59.4 percent. With thinking mode enabled on its hardest benchmark, the model consumes roughly 249,000 completion tokens per trajectory.
How was it trained, and how fast was it shipped?
Pre-training began May 22, and the model launched in under nine weeks, trained on 4,096 Nvidia H200 GPUs. Poolside has now shipped three models in three months.
Why is Poolside releasing it now?
Poolside frames the release as a response to the dominance of Chinese open-weight labs, naming DeepSeek, Qwen, Kimi, GLM, MiniMax, and Tencent Hunyuan. The company notes that Laguna S 2.1 occupies a size class into which no Western lab has released open weights in 11 months, since OpenAI’s gpt-oss-120b last August.
What are the leaders saying?
Co-CEO Jason Warner said, “The West needs open-weight models it can trust, run, and build on.” Co-founder and co-CEO Eiso Kant wrote on X, “I believe intelligence should and will become a commodity.”
Who can use Laguna S 2.1, and on what terms?
Anyone can download the weights from Hugging Face under the OpenMDW-1.1 license, which the company describes as permissive. Because only 8 billion parameters activate per token, the model can run on a single Nvidia DGX Spark, lowering the hardware bar for self-hosting.
FAQ
What is Laguna S 2.1?
Laguna S 2.1 is a 118-billion-parameter Mixture-of-Experts coding model released by Poolside on July 21, 2026. It activates 8 billion parameters per token, supports a 1 million token context window, and is available on Hugging Face under the OpenMDW-1.1 license.
How does Laguna S 2.1 compare to larger coding models?
On Terminal-Bench 2.1 it scores 70.2 percent, ahead of DeepSeek-V4-Pro-Max at 64.0, Thinking Machines Inkling at 63.8, and Nvidia Nemotron 3 Ultra at 56.4. It also scores 78.5 percent on SWE-Bench Multilingual and 59.4 percent on SWE-Bench Pro.
Why is Poolside highlighting open weights?
Poolside positions the release as a Western response to leading Chinese open-weight labs, noting that no Western lab has released open weights in this size class for 11 months, since OpenAI’s gpt-oss-120b. Co-CEO Jason Warner said the West needs open-weight models it can trust, run, and build on.