Model release

d1-3B

Release in the Liquid AI d1 family · version d1-3B

d1-3B is a 3.12-billion-parameter multimodal decision model from Liquid AI, post-trained from its LFM2.5-VL-3B vision-language model. It accepts text, JSON, and images with a 32,768-token context and answers named questions in one forward pass without generating output tokens; the card says it is not a chat model.2 1Fact reviewed Oct 11, 2026

Model hub: Model card (Hugging Face) (external site: huggingface.co)
Release notes: Open d1 announcement (external site: liquid.ai)
License: License (LFM Open License v1.0) (external site: huggingface.co)

Last reviewedOct 11, 2026Entry updated Oct 11, 2026Documented release Oct 7, 2026

Availability and license

Overall availability

Public

Weights download from Hugging Face without an access gate; use is governed by the LFM Open License v1.0, which conditions commercial-use rights on the licensee's legal entity not exceeding a threshold defined as annual revenue of US$10,000,000 or more.3 4

Availability fact review: Oct 11, 2026

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

LFM Open License v1.0 (external site: huggingface.co)4 3
Applies to: Weights · custom license (no SPDX identifier) · fact reviewed Oct 11, 2026
Plain-language guide to the LFM Open License v1.0

Custom Liquid AI license (card license field "lfm1.0") modeled on Apache 2.0; the file is the same text as the LFM2.5-2.6B license already recorded in this catalog. Commercial rights are conditional on the licensee's legal entity not exceeding a "Threshold" of US$10,000,000 or more in annual revenue, and commercial use by a legal entity above the Threshold is not licensed; the Threshold does not apply to a qualified non-profit organization's non-commercial or research use. The repository's custom model code (loaded with trust_remote_code) has no separate license file.4 3Fact reviewed Oct 11, 2026

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 d1-3B
Item	Status	Notes and evidence
WeightsCan the general public download the model parameters for this release?	Public	A single safetensors file in the ungated Hugging Face repository.3
Inference codeIs code for running the model published?	Public	The repository ships its own modeling code for Transformers (version 5.14 or later, loaded with trust_remote_code), and the card documents system_one and batch calls.2 3
Training codeIs the code used to train the model published?	Unknown	No training code was found in the model card or announcement.
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	The sources reviewed do not describe the training data.
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.	Unknown	Not assessed.
Training recipeAre the training configuration and procedure documented in enough detail to follow?	Partial	The announcement describes the approach at a high level: merging weights of LFM2.5-2.6B and the LFM2.5-VL-3B text backbone, then fine-tuning checkpoints with different seeds and data mixtures and merging them again. No hyperparameters are given.1
Evaluation materialsPublic = evaluation code or prompts that let others re-run the evaluations are published. Partial = results only.	Partial	The card and announcement report results on named benchmarks; evaluation code was not identified.2 1

What it is useful for

Yes/no, multiple-choice, and rating decisions inside a pipeline: routing and triage, moderation, intent and topic classification, extraction checks, reranking, judge-style scoring, agent guardrails, and visual inspection, per the model card.2Fact reviewed Oct 11, 2026

Organization context

Liquid AI

Provenance and derivatives

Post-trained by Liquid AI from its LFM2.5-VL-3B vision-language model, which the card lists as the base model; the card names the vision encoder as SigLIP2 NaFlex (shape-optimized, 400M).2 3 1

Derived from: LFM2.5-VL-3B (external site: huggingface.co) — Base model (Liquid AI).

Other releases in the Liquid AI d1 family

No other releases in this family have been assessed.

Liquid AI d1 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.
Legacy data assessment (v0.1): 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.-governed project

Developed and published by Liquid AI in its Hugging Face organization; the license file names Liquid AI, Inc. as licensor. Liquid AI gives its address as Cambridge, Massachusetts (see the liquid-ai record).1 2 4

Assessed Oct 11, 2026

Sources

1.
Open d1: Edge decision models for text, vision, and audio (external site: liquid.ai)
Liquid AI · Announcement · published Oct 7, 2026 · accessed Oct 11, 2026
2.
LiquidAI/d1-3B model card (external site: huggingface.co)
Liquid AI (Hugging Face) · Model card · accessed Oct 11, 2026
3.
LiquidAI/d1-3B (Hugging Face model API metadata) (external site: huggingface.co)
Hugging Face · Other · accessed Oct 11, 2026
4.
LiquidAI/d1-3B LICENSE (LFM Open License v1.0) (external site: huggingface.co)
Liquid AI (Hugging Face) · License · accessed Oct 11, 2026

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APA style

USASI. (2026, October 11). d1-3B. United States of America Superintelligence. https://unitedstatesofamericasuperintelligence.com/open/liquid-d1-3b/

BibTeX

@misc{usasi_liquid_d1_3b,
  author = {{USASI}},
  title = {d1-3B},
  year = {2026},
  month = oct,
  howpublished = {\url{https://unitedstatesofamericasuperintelligence.com/open/liquid-d1-3b/}},
  note = {United States of America Superintelligence. Last updated 2026-10-11}
}

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