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ease
features
design
support

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Description

Apollo is a streamlined mobile application that facilitates completely on-device, cloud-independent AI interactions, allowing users to interact with sophisticated language and vision models in a secure, private manner with minimal delays. It features a collection of compact foundation models sourced from the company's LEAP platform, enabling users to compose messages, send emails, converse with a personal AI assistant, create digital characters, or utilize image-to-text functions, all while maintaining offline capabilities and ensuring no data is transmitted beyond the device. Optimized for immediate responsiveness and offline functionality, Apollo guarantees that all inference occurs locally, eliminating the need for API calls, external servers, or logging of user data. This application acts as both a personal AI exploration tool and a development environment for those utilizing LEAP models, allowing users to effectively assess a model's performance on their specific mobile devices prior to more widespread implementation. Additionally, Apollo's design emphasizes user autonomy, ensuring a seamless experience free from external interruptions or privacy concerns.

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.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon Bedrock
ElevenLabs
Gemma 3
Gemma 4
Hugging Face
LEAP
Liquid AI
Llama
Llama 3.2
OpenRouter
Qwen3

Integrations

Amazon Bedrock
ElevenLabs
Gemma 3
Gemma 4
Hugging Face
LEAP
Liquid AI
Llama
Llama 3.2
OpenRouter
Qwen3

Pricing Details

Free
Free Trial
Free Version

Pricing Details

Free
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/apollo

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

Product Features

Product Features

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