Poolside Releases Laguna-M.1, an Open MoE Model
The AI coding startup steps into open weights with an Apache-2.0 mixture-of-experts model built for text and code.
Poolside, the startup best known for its work on AI-assisted software development, has published its first open-weights model. Laguna-M.1 arrives on Hugging Face as a mixture-of-experts (MoE) language model aimed at both general text and code generation, released under the permissive Apache-2.0 license.
The model ships with support for two of the most widely used high-throughput inference engines, vLLM and SGLang. That choice signals a focus on practical deployment: teams can run Laguna-M.1 on their own infrastructure without waiting for community patches, which lowers the barrier for evaluation and production testing alike.
Why it matters
Poolside has largely built its reputation behind a closed product, so an openly licensed release is a notable shift. A few reasons it stands out:
- Permissive licensing: Apache-2.0 allows commercial use and modification, making the model viable for internal tooling.
- MoE architecture: Mixture-of-experts designs activate only a fraction of parameters per token, a common route to balancing capability and serving cost.
- Day-one tooling: Built-in vLLM and SGLang compatibility means the model is ready to serve from the start.
Key specifics—including parameter counts, active-expert configuration, and context length—are not detailed in the release record, so prospective users will want to check the model card directly before benchmarking. As an initial release, Laguna-M.1 establishes a baseline for what could become a recurring open-model line from Poolside, and a fresh option for developers weighing open alternatives for coding workloads.
Sources
- Visit
poolside/Laguna-M.1
Hugging Face
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