Model release

Laguna XS 2.1

Laguna XS 2.1 is an open-weight model release in the Laguna family from Poolside1, version XS 2.1, released Jul 2, 2026. Its weights can be downloaded by the public1 5 under the OpenMDW License Agreement, version 1.12 1.

Laguna XS 2.1 is a mixture-of-experts model with 33B total and 3B active parameters per token, built for agentic coding on a local machine. Poolside describes it as an upgraded version of Laguna XS.2 with the same architecture. It supports interleaved reasoning between tool calls and has a 262,144-token context window.1 5

Model hub: Model card (external site: huggingface.co)
License: License (OpenMDW-1.1) (external site: huggingface.co)
Release notes: Release announcement (external site: poolside.ai)
Paper: Laguna M.1/XS.2 technical report (external site: poolside.ai)

On AI on Hugging Face: poolside/Laguna-XS.2, poolside/Laguna-XS-2.1

Last reviewedSep 29, 2026Entry updated Sep 29, 2026Documented release Jul 2, 2026

Availability and license

Overall availability

Public

Weights download from Hugging Face without an access gate. Also served through the Poolside API and OpenRouter.1 5

Availability fact review: not separately recorded

Availability is separate from permission: read the license before using or redistributing.

OpenMDW License Agreement, version 1.1 (external site: huggingface.co)2 1
Applies to: Weights and code · custom license (no SPDX identifier) · fact-level rights review not recorded
Plain-language guide to the OpenMDW License Agreement, version 1.1

OpenMDW-1.1 grants broad use rights and places no restrictions on outputs. It requires keeping the license and notices when redistributing, and ends the rights of anyone who sues claiming the materials infringe a patent or copyright. The predecessor, Laguna XS.2, is published under Apache 2.0. The model card asks users to follow Poolside's Acceptable Use Policy.2 1 4

Component reuse rights

A readable or downloadable component is not automatically reusable. These indicators concern recorded license evidence, not system certification.

weights: Unknown — no complete fact-level rights review
code: Unknown — no complete fact-level rights review
data: Unknown — no complete fact-level rights review
documentation: Unknown — no complete fact-level rights review

No complete system-rights review is recorded for this release.

Model-disclosure tier

Computed from the checklist below using USASI rubric v0.2. An editorial category, not a certification.

Open-weight

The model parameters for this release can be downloaded by the public. License terms may still restrict use, redistribution, or commercial use.

The weights are under a license that is not on the rubric's OSI-approved list. Read its terms before use.

How tiers are computed

Public materials checklist

Items for a model under USASI rubric v0.2. Unknown means unassessed or insufficient evidence.

Public materials checklist for Laguna XS 2.1
Item	Status	Notes and evidence
WeightsCan the general public download the model parameters for this release?	Public	BF16 weights are in the ungated repository; FP8, NVFP4, and INT4 variants are published as a collection.1 5
Inference codeIs code for running the model published?	Public	The repository includes modeling code (modeling_laguna.py), and the model card documents vLLM, SGLang, Transformers, TensorRT-LLM, llama.cpp, and Ollama.1 3
Training codeIs the code used to train the model published?	Unknown	Not assessed.
Training-data informationDoes the information cover provenance, scope, acquisition, selection, labeling, processing, and where data or alternatives can be obtained? Access alone does not establish completeness.	Unknown	Not assessed.
Training-data accessCan the training data be obtained? This is independent of information completeness and reuse rights; original unshareable data need not be downloadable.	Unknown	Not assessed.
Complete training pipelineIs the complete base-training and preprocessing pipeline published, including configuration? Fine-tuning code or an inference SDK alone is insufficient.	Unknown	Not assessed.
Legacy data assessment (v0.1)Historical assessment combining download access and disclosure. Preserved for traceability; excluded from the v0.2 tier calculation. See the new separate assessments above.	Partial	The model card points to the Laguna M.1/XS.2 technical report, which describes the XS.2 pre-training mix (web, code, curated educational and academic text, and synthetic data). Any data changes for XS 2.1 are not described, and no public data release was found.1 7
Training recipeAre the training configuration and procedure documented in enough detail to follow?	Partial	The technical report documents XS.2 pre-training, supervised fine-tuning, and agentic reinforcement learning. The changes made for XS 2.1 are summarized, not specified.7 1
Evaluation materialsPublic = evaluation code or prompts that let others re-run the evaluations are published. Partial = results only.	Partial	The model card publishes benchmark results with the harness, sampling settings, and sandbox resources used.1

What it is useful for

Poolside documents it for agentic coding and long-horizon work on local machines, used through its agent CLI, OpenAI-compatible API integrations, or local runtimes such as Ollama and MLX.1 6

Run and use notes

Documented facts only. No hardware or performance claims are made without a cited source and stated assumptions.

The model card documents support in vLLM, SGLang, Transformers, TensorRT-LLM, and llama.cpp, plus Ollama (with MLX) and mlx-lm for local use on a Mac. It notes a pending llama.cpp fix for empty output with Ollama on Apple Silicon.1

Organization context

Poolside

Provenance and derivatives

The model card describes Laguna XS 2.1 as an upgraded version of Laguna XS.2. The technical report states that XS.2 was trained from scratch by Poolside.1 7

Derived from: Laguna XS.2 (external site: huggingface.co) — Same organization; earlier release in the family.

Other releases in the Laguna family

Laguna S 2.1Model-disclosure tier (USASI rubric v0.2): Open-weight

Laguna family overview

What this catalog does not know

Unknown means the sources reviewed for this record do not document it. It is not evidence that something does not exist.

Training code: unknown.
Training-data information: unknown.
Training-data access: unknown.
Complete training pipeline: unknown.

Have a primary source? How to report a correction.

U.S. eligibility

Project eligibility rests on documented governing or maintaining entities, not on contributors.

Eligible · basis: U.S. headquarters

Developed and published by Poolside, Inc., which states that it is headquartered in San Francisco. See the poolside organization record for the assessment of its French presence. It updates Laguna XS.2, which Poolside's technical report says it trained from scratch.8 1 7

Assessed Sep 29, 2026

Sources

1.
poolside/Laguna-XS-2.1 model card (external site: huggingface.co)
Poolside · Model card · accessed Sep 29, 2026
2.
Laguna-XS-2.1 LICENSE.md (OpenMDW-1.1) (external site: huggingface.co)
Poolside · License · accessed Sep 29, 2026
3.
Laguna-XS-2.1 repository file listing (external site: huggingface.co)
Hugging Face · Repository · accessed Sep 29, 2026
4.
poolside/Laguna-XS.2 model card (external site: huggingface.co)
Poolside · Model card · accessed Sep 29, 2026
5.
Introducing Laguna XS 2.1 (external site: poolside.ai)
Poolside · Announcement · published Jul 2, 2026 · accessed Sep 29, 2026
6.
Model release notes (external site: docs.poolside.ai)
Poolside · Release notes · accessed Sep 29, 2026
7.
Laguna M.1/XS.2 Technical Report (external site: poolside.ai)
Poolside · Paper · published May 25, 2026 · accessed Sep 29, 2026
8.
Poolside releases Laguna S 2.1, the West's most capable open-weight model (external site: globenewswire.com)
Poolside via GlobeNewswire · Announcement · published Jul 21, 2026 · accessed Sep 29, 2026

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Cite this page

APA style

USASI. (2026, September 29). Laguna XS 2.1. United States of America Superintelligence. https://unitedstatesofamericasuperintelligence.com/open/laguna-xs-2-1/

BibTeX

@misc{usasi_laguna_xs_2_1,
  author = {{USASI}},
  title = {Laguna XS 2.1},
  year = {2026},
  month = sep,
  howpublished = {\url{https://unitedstatesofamericasuperintelligence.com/open/laguna-xs-2-1/}},
  note = {United States of America Superintelligence. Last updated 2026-09-29}
}

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