Today we’re releasing Laguna S 2.1, a significant step forward in our development of models that pursue longer horizon work and make effective use of reasoning.

Laguna S 2.1 is a 118B total parameter Mixture-of-Experts (MoE) model with 8B activated parameters per token and supports a context window of up to 1M tokens in thinking and no-thinking modes. It went from the start of training to launch in under nine weeks, and on long-horizon coding benchmarks it holds its own against models many times its size. For every benchmark score we publish today, we are releasing full trajectories for every trial in the final evaluation set at trajectories.poolside.ai .

Laguna S 2.1 118B-A8B

Tencent Hy3 295B-A21B

Inkling 975B-A41B

Nemotron 3 Ultra 550B-A55B

DeepSeek-V4-Pro-Max 1.6T-A49B

Kimi K3 2.8T-A50B

Qwen 3.7 Max —

Muse Spark 1.1 —

Claude Fable 5 —

Terminal-Bench 2.1 Resolved tasks on Terminal-Bench 2.1.

SWE-Bench Multilingual Resolved tasks on SWE-Bench Multilingual.

SWE-Bench Pro (Public Dataset)…