Laguna S 2.1

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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.