mlsanityData to 14 Oct 2026

Laguna M.1/XS.2 Technical Report

arXiv 2605.27605 ↗First posted 26 May 2026cs.AI cs.SEcited by 1

On the map: LLM agents and tool use → Software engineering coding agents

also in 1 more
Abstract (arXiv)

We present Laguna M.1 and Laguna XS.2, two Mixture-of-Experts foundation models built for long-horizon, agentic coding: M.1 has 225.8B total parameters (23.4B activated per token) and XS.2 has 33.4B total (3B activated). Both models were trained from scratch end-to-end inside the same internal system that we refer to as our Model Factory: a tightly-integrated stack of versioned data, training, evaluation, and inference components that turn model development into an industrial process. We describe the principles and design choices of the Model Factory and also detail the end-to-end training process of our models, throughout pre-training data and architecture, post-training stages, evaluation, and quantization. On agentic software engineering and terminal benchmarks (SWE-bench Verified, SWE-bench Multilingual, SWE-Bench Pro, and Terminal-Bench 2.0) M.1 and XS.2 are competitive with state-of-the-art open models in their respective weight classes. Laguna XS.2 weights are released under Apache~2.0 at https://huggingface.co/collections/poolside/laguna-xs2.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use. Builds on 72 of its 98 references that are in the map. First posted on arXiv 26 May 2026.

Builds on

72 of 98 references.

Closest ancestors · 4

Same direction, newest first

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  3. 2024OpenHands: An Open Platform for AI Software Developers as Generalist Agents23 Jul
  4. 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation16 Aug

Other references · 68

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