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Laguna XS.2 and M.1

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Why This Matters

The release of Laguna XS.2 and M.1 marks a significant advancement in agentic coding models, offering powerful tools for long-horizon tasks and software development. By providing open access to Laguna XS.2 weights, the company fosters innovation and collaboration within the research community, potentially accelerating the development of more capable AI agents. This move signals a shift toward more expressive and autonomous AI systems that can write and execute code, transforming how AI interacts with and automates complex tasks.

Key Takeaways

We’ve released the first two models in the Laguna family, Laguna M.1 and Laguna XS.2, alongside the runtime we use to train and operate agents, available through two product experiences in preview.

Laguna M.1 came first, finishing pre-training at the end of last year; it's the foundation for everything else we're building across the family. Laguna XS.2 is a much smaller model, but remarkably capable for its size, and it's our first open-weight release. Both models are free to use for a limited time via our API and on OpenRouter, and Laguna XS.2 weights are also available under an Apache 2.0 license.

Laguna XS.2 and Laguna M.1 are agentic coding models built for long-horizon work. To date, we’ve been focused on serving our government and public sector clients with capable models deployable into the highest-security environments. And while our commitment to these customers remains, we’re now ready to share where we are with the world. We’re also excited to release the weights of Laguna XS.2, our newest generation model, to the open ecosystem to support builders and the wider research community.

We're working toward models that enable more capable agents; and we believe the path runs through coding capability and increasingly long-horizon tasks. Creating software is the core skill through which many other capabilities get expressed.

Today, most agents interact with the world through tool calling, where structured interfaces restrict agents to a fixed set of actions defined in advance. We think this is a transitional pattern. Software is a much more expressive interface. An agent that can write and execute code can compose actions, parallelize work, and build its own ad-hoc systems to interact with the world.

These models are the work of the roughly 60 people who make up our Applied Research organization, across architecture, data, pre-training, and reinforcement learning. We're excited to bring this work into the world and see what the community builds with it.

Laguna M.1 225B-A23B

Laguna XS.2 33B-A3B

Qwen3.5 397B-A17B

Qwen3.5 35B-A3B

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