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features
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support

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Description

LFM3 represents Liquid AI's suite of streamlined, open-weight foundational models designed for a variety of applications, including text, vision, audio, and multimodal tasks. This lineup features variants for text generation, vision-language processing, audio, omni tasks, and decision-making models. Developers have the option to download the model weights, customize the supported models via fine-tuning, and deploy them on local edge hardware, or alternatively, utilize Liquid AI’s hosted API for access. Potential applications encompass conversational agents, tool invocation, speech transcription and synthesis, understanding of images and videos, document extraction, classification, routing, and robotics functionalities. LFM3 aims to cater to developers, researchers, and organizations focused on creating tailored AI solutions that require adaptable deployment options, including the ability for local inference. Furthermore, the open-weight models operate under Liquid AI’s LFM Open License, where the eligibility for commercial use and its associated terms are contingent upon the annual revenue of the organization. This flexibility allows users to tailor their AI implementations precisely to their needs, enhancing the overall utility of the models.

Description

Ling 3.0 Tiny is a reasoning model featuring open weights, comprising 7.9 billion total parameters and 1.3 billion active parameters, alongside a substantial context window of 262,000 tokens. Leveraging a mixture-of-experts architecture, it pushes the boundaries of the open-weights Pareto frontier in terms of intelligence relative to active parameters, while being compact enough for local deployment in various environments. Scoring 25 on the Artificial Analysis Intelligence Index, it stands on par with gpt-oss-120b, which scores 24, despite utilizing 15 times fewer total parameters and 4 times fewer active parameters. This impressive parameter efficiency does come with a trade-off, as it requires a significant 213 million output tokens to complete the Intelligence Index evaluation. In addition, Ling 3.0 Tiny exhibits noteworthy advancements in reducing hallucination tendencies compared to Ling-mini-2.0; it enhances its AA-Omniscience score by 59 points while keeping accuracy levels consistent. Notably, rather than making random guesses in uncertain situations, the model chose to attempt only 37% of the questions during evaluation, leading to a markedly reduced hallucination rate of 30%, a significant improvement over the previous generation's 96%. This strategic approach not only demonstrates the model's improved reasoning capabilities but also highlights its potential for more reliable real-world applications.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

OpenRouter Yes 
Claude Code No 
Hermes Agent No 
Hugging Face Yes 
Hugging Face Transformers Yes 
Kilo Code No 
LM Studio Yes 
Ollama Yes 
OpenClaw No 
Unsloth Yes 
Vercel AI Gateway Yes 
ZenMux No 
vLLM Yes 

Integrations

OpenRouter Yes 
Claude Code Yes 
Hermes Agent Yes 
Hugging Face No 
Hugging Face Transformers No 
Kilo Code Yes 
LM Studio No 
Ollama No 
OpenClaw Yes 
Unsloth No 
Vercel AI Gateway No 
ZenMux Yes 
vLLM No 

Pricing Details

$0.08/MTok
LFM3-1.7B API usage is $0.08 per million input tokens, $0.02 per million cached input tokens, and $0.20 per million output tokens. New organizations receive $2 in API credit. Open-weight models can be used in production free by developers, researchers, nonprofits, and businesses with less than $10 million in annual revenue; businesses above that threshold require a paid license.
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Liquid AI

Founded

2023

Country

United States

Website

www.liquid.ai/blog/lfm3

Vendor Details

Company Name

Ant Group

Founded

2014

Country

China

Website

ant-ling.com

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