Laguna XS.2 and M.1

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.

Laguna M.1 is our most capable model to date. It's a 225B total parameter Mixture of Experts (MoE) model with 23B activated parameters, trained completely in-house and from scratch on 30T tokens, using 6,144 interconnected NVIDIA Hopper GPUs. Laguna M.1 reaches 46.9% on SWE-bench Pro and 40.7% on Terminal-Bench 2.0.

Laguna XS.2 is our second-generation MoE and our first open-weight model. At 33B total parameters with 3B activated (30T tokens trained), it's a highly capable open-weight agentic coding model in its weight class, reaching 44.5% on SWE-bench Pro and 30.1% on Terminal-Bench 2.0. The weights are available for download today under Apache 2.0.

Every aspect of our Laguna series was conducted on NVIDIA hardware. Additionally, Laguna XS.2 is supported in NVIDIA TensorRT-LLM on Day 1. We're also providing an NVFP4 version of Laguna XS.2 for strong performance on NVIDIA Blackwell architecture.