Poolside新出的Laguna S 2.1模型，稀疏MoE只激活8B就能达到1M上下文，还能本地跑在DGX Spark上，写代码和长期任务都很顺手。
Poolside发布Laguna S 2.1，一个118B参数的稀疏MoE开放权重模型，每token仅激活8B参数。模型支持高达1M的上下文长度，并同时提供思考与非思考两种模式，基准为OpenMDW-1.1。该模型专为智能编码和长期任务设计，具备规划、工具调用和自我纠错能力。官方NVFP4量化版本可在单台NVIDIA DGX Spark上本地运行。
🎉 Congrats to @poolsideai on Laguna S 2.1, a new o…
🎉 Congrats to @poolsideai on Laguna S 2.1, a new open-weight model built for agentic coding and long-horizon work.
🧠 118B sparse MoE, only 8B active per token, up to 1M context, thinking + no-thinking modes, OpenMDW-1.1
🔁 Built to stay on task across long, multi-step runs: plan, call tools, check its work, recover, keep going
🖥️ The official NVFP4 quant runs locally on a single @NVIDIAAI DGX Spark
This model is a scale up of the Laguna XS 2.1 architecture and vLLM runs it out of the box. Keep your existing Laguna serve setup, and the poolside_v1 tool-call and reasoning parsers already work.