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ease
features
design
support

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Description

Liquid AI's LFM2.5 represents an advanced iteration of on-device AI foundation models, engineered to provide high-efficiency and performance for AI inference on edge devices like smartphones, laptops, vehicles, IoT systems, and embedded hardware without the need for cloud computing resources. This new version builds upon the earlier LFM2 framework by greatly enhancing the scale of pretraining and the stages of reinforcement learning, resulting in a suite of hybrid models that boast around 1.2 billion parameters while effectively balancing instruction adherence, reasoning skills, and multimodal functionalities for practical applications. The LFM2.5 series comprises various models including Base (for fine-tuning and personalization), Instruct (designed for general-purpose instruction), Japanese-optimized, Vision-Language, and Audio-Language variants, all meticulously crafted for rapid on-device inference even with stringent memory limitations. These models are also made available as open-weight options, facilitating deployment through platforms such as llama.cpp, MLX, vLLM, and ONNX, thus ensuring versatility for developers. With these enhancements, LFM2.5 positions itself as a robust solution for diverse AI-driven tasks in real-world environments.

Description

gpt-oss-20b is a powerful text-only reasoning model consisting of 20 billion parameters, made available under the Apache 2.0 license and influenced by OpenAI’s gpt-oss usage guidelines, designed to facilitate effortless integration into personalized AI workflows through the Responses API without depending on proprietary systems. It has been specifically trained to excel in instruction following and offers features like adjustable reasoning effort, comprehensive chain-of-thought outputs, and the ability to utilize native tools such as web search and Python execution, resulting in structured and clear responses. Developers are responsible for establishing their own deployment precautions, including input filtering, output monitoring, and adherence to usage policies, to ensure that they align with the protective measures typically found in hosted solutions and to reduce the chance of malicious or unintended actions. Additionally, its open-weight architecture makes it particularly suitable for on-premises or edge deployments, emphasizing the importance of control, customization, and transparency to meet specific user needs. This flexibility allows organizations to tailor the model according to their unique requirements while maintaining a high level of operational integrity.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

AgentSea
AiAssistWorks
Amazon Bedrock
Dessix
ElevenLabs
Gemma 3
Gemma 4
Google Antigravity
Hugging Face
Inworld TTS
LEAP
Llama
Llama 3.2
Microsoft Foundry
Nebius Token Factory
Ollama
OpenAI
Python
Tinfoil
Together AI

Integrations

AgentSea
AiAssistWorks
Amazon Bedrock
Dessix
ElevenLabs
Gemma 3
Gemma 4
Google Antigravity
Hugging Face
Inworld TTS
LEAP
Llama
Llama 3.2
Microsoft Foundry
Nebius Token Factory
Ollama
OpenAI
Python
Tinfoil
Together AI

Pricing Details

Free
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Liquid AI

Founded

2023

Country

United States

Website

www.liquid.ai/blog/introducing-lfm2-5-the-next-generation-of-on-device-ai

Vendor Details

Company Name

OpenAI

Founded

2015

Country

United States

Website

openai.com/index/gpt-oss-model-card/

Product Features

Product Features

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