Model release

LFM2.5-2.6B

LFM2.5-2.6B is an open-weight model release in the LFM (Liquid Foundation Models) family from Liquid AI1 4, version LFM2.5-2.6B, released Aug 4, 2026. Its weights can be downloaded by the public1 under the LFM Open License v1.02 1.

A 2.69B-parameter text-only hybrid model with 30 layers (22 double-gated short-convolution blocks and 8 grouped-query attention blocks), a 131,072-token context window, and support for 16 languages. Liquid AI pretrained it on about 34 trillion tokens and post-trained it for agentic use; it always reasons before answering.1 4

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

On AI on Hugging Face: LiquidAI/LFM2.5-2.6B

Last reviewedSep 29, 2026Entry updated Sep 29, 2026Documented release Aug 4, 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.1 2

Availability fact review: not separately recorded

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

LFM Open License v1.0 (external site: huggingface.co)2 1
Applies to: Weights · custom license (no SPDX identifier) · fact-level rights review not recorded
Plain-language guide to the LFM Open License v1.0

Custom Liquid AI license (card license field "lfm1.0") modeled on Apache 2.0, with the same text as the other LFM2.5 releases reviewed. Commercial rights are conditional on the licensee's legal entity not exceeding a "Threshold" defined as annual revenue of US$10,000,000 or more, and commercial use by a legal entity that exceeds the Threshold is not licensed; the Threshold does not apply to a qualified non-profit organization's use for non-commercial or research purposes. The license also requires redistributors to include it and mark modified files, and ends patent rights for anyone who files patent litigation over the work.2 3

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 LFM2.5-2.6B
Item	Status	Notes and evidence
WeightsCan the general public download the model parameters for this release?	Public	Ungated safetensors weights on Hugging Face; GGUF, ONNX, and MLX conversions and a base checkpoint are published as separate repositories.1
Inference codeIs code for running the model published?	Public	The model card documents inference with Hugging Face Transformers (5.0.0 or later), vLLM, SGLang, llama.cpp, MLX, and LM Studio, and gives setup examples for several agent harnesses.1
Training codeIs the code used to train the model published?	Unknown	No training code release was found in the model card or release post.
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.	Unknown	The model card and release post state the pretraining budget (about 34 trillion tokens) but do not describe data sources or composition.
Training recipeAre the training configuration and procedure documented in enough detail to follow?	Partial	The model card and release post describe the stages at a high level: pretraining, a mid-training phase that extends context to 128K, two rounds of supervised fine-tuning, per-domain teacher specialization, multi-domain on-policy distillation, and agentic reinforcement learning inside agent harnesses. Hyperparameters and data mixes are not given.1 4
Evaluation materialsPublic = evaluation code or prompts that let others re-run the evaluations are published. Partial = results only.	Partial	The model card reports a benchmark table against other small models; evaluation code or prompts are not linked.1

What it is useful for

The model card recommends it for agentic workloads, tool use, data extraction, retrieval-augmented generation, and long-context workflows, and does not recommend it for agentic coding or knowledge-heavy tasks.1

Run and use notes

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

The model card recommends temperature 0.1, top_k 50, and repetition_penalty 1.1, and shows Transformers loading in bfloat16. It points to a separate 328M speculative-decoding drafter, LFM2.5-2.6B-DSpark, for SGLang and Apple silicon.1

Organization context

Liquid AI

Provenance and derivatives

Post-trained by Liquid AI from its own LFM2.5-2.6B-Base checkpoint; no third-party base model is involved.1

Derived from: LFM2.5-2.6B-Base (external site: huggingface.co) — Same organization; pretrained base checkpoint.

Other releases in the LFM (Liquid Foundation Models) family

LFM2.5-24B-A2BModel-disclosure tier (USASI rubric v0.2): Open-weight
LFM2.5-8B-A1BModel-disclosure tier (USASI rubric v0.2): Open-weight

LFM (Liquid Foundation Models) 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. headquarters

Developed and published by Liquid AI, Inc., the licensor named in the model's license file. Liquid AI gives its address as Cambridge, Massachusetts (see the liquid-ai record).1 2 5

Assessed Sep 29, 2026

Sources

1.
LiquidAI/LFM2.5-2.6B model card (external site: huggingface.co)
Liquid AI · Model card · accessed Sep 29, 2026
2.
LFM2.5-2.6B LICENSE (LFM Open License v1.0) (external site: huggingface.co)
Liquid AI · License · accessed Sep 29, 2026
3.
LFM License (external site: liquid.ai)
Liquid AI · License · accessed Sep 29, 2026
4.
LFM2.5-2.6B: Deploy Agents Everywhere (external site: liquid.ai)
Liquid AI · Announcement · published Aug 4, 2026 · accessed Sep 29, 2026
5.
Liquid AI Privacy Policy (external site: liquid.ai)
Liquid AI · Official page · published Jul 14, 2025 · accessed Sep 29, 2026

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This listing is not an endorsement, a safety assessment, or a federal approval.

Cite this page

APA style

USASI. (2026, September 29). LFM2.5-2.6B. United States of America Superintelligence. https://unitedstatesofamericasuperintelligence.com/open/lfm2-5-2-6b/

BibTeX

@misc{usasi_lfm2_5_2_6b,
  author = {{USASI}},
  title = {LFM2.5-2.6B},
  year = {2026},
  month = sep,
  howpublished = {\url{https://unitedstatesofamericasuperintelligence.com/open/lfm2-5-2-6b/}},
  note = {United States of America Superintelligence. Last updated 2026-09-29}
}

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