# 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.

Published by The Open Weights on Jun 15, 2026. Canonical: https://theopenweights.com/news/laguna-m-1-ldp1

## Key facts

- Company: Poolside
- Model: Laguna-M.1
- Version: M.1
- Category: Text / LLM
- Modalities: Code, Text / LLM
- License: Apache 2.0 (Open weights, commercial use allowed)
- Active parameters: 23B
- Context window: 262K tokens
- Architecture: LagunaForCausalLM
- Precision: BF16
- Weights size: 451.6 GB
- Significance: notable
- Published: 2026-06-15
- Last verified: 2026-06-26
- Hugging Face: https://huggingface.co/poolside/Laguna-M.1
- Canonical URL: https://theopenweights.com/news/laguna-m-1-ldp1

Poolside, the startup best known for its work on AI-assisted software development, has published its first open-weights model. [Laguna-M.1](https://huggingface.co/poolside/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](https://huggingface.co/poolside/Laguna-M.1) 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.

## Get the model

- [Hugging Face](https://huggingface.co/poolside/Laguna-M.1)

## Sources

- [poolside/Laguna-M.1](https://huggingface.co/poolside/Laguna-M.1) — Hugging Face, Jun 15, 2026

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Source: The Open Weights (https://theopenweights.com/). Aggregated and written by Claude, curated by humans. Cite as: "Poolside Releases Laguna-M.1, an Open MoE Model", The Open Weights, Jun 15, 2026, https://theopenweights.com/news/laguna-m-1-ldp1