Laguna S 2.1

ZML - Model to Metal Blog LLMD GitHub 3.5K Docs Discord Contact Back to posts Article Poolside's open-weight model for agentic coding and long-horizon work. July 21, 2026 inference / performance / NVIDIA / AMD / TPU / Intel / Apple / Metal / poolside / laguna In close collaboration with Poolside, we’re happy to announce the support of Laguna S 2.1, their new open-weight model for agentic coding and long-horizon work. It is a 118B total parameters Mixture-of-Experts model with 8B activated parameters per token and supports a context window of up to 1M tokens, available in thinking and no-thinking modes. And it’s available today in ZML/LLMD with DFlash support. Most importantly (and as always with us), it’s available on all the supported platforms: NVIDIA, AMD, Intel, Google TPU and Apple Metal. Run it today NVIDIA docker run -p 8000:8000 --shm-size=256GB --gpus=all -e HF_TOKEN -it zmlai/llmd:cuda \ --model=hf://poolside/Laguna-S-2.1 \ --dflash-model=hf://poolside/Laguna-S-2.1-DFlash AMD docker run -p 8000:8000 --shm-size=256GB --device=/dev/kfd --device=/dev/dri -e HF_TOKEN -it zmlai/llmd:rocm \ --model=hf://poolside/Laguna-S-2.1 \ --dflash-model=hf://poolside/Laguna-S-2.1-DFlash Intel docker run -p 8000:8000 --device=/dev/dri -e HF_TOKEN -it zmlai/llmd:oneapi \ --model=hf://poolside/Laguna-S-2.1 \ --dflash-model=hf://poolside/Laguna-S-2.1-DFlash Google TPU docker run --net=host --privileged -e HF_TOKEN -it zmlai/llmd:tpu \ --model=hf://poolside/Laguna-S-2.1 \ --dflash-model=hf://poolside/Laguna-S-2.1-DFlash Apple Metal brew install zml/zml/llmd llmd --model=hf://poolside/Laguna-S-2.1 --dflash-model=hf://poolside/Laguna-S-2.1-DFlash Benchmarks It’s a good model, sir.