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What is Locally AI?
Locally AI is a cutting-edge application that enables users to harness the power of advanced language models directly on their iPhones, iPads, or Macs without relying on cloud services or an internet connection. Utilizing Apple’s MLX framework, it offers rapid performance while maintaining low power consumption, which results in a seamless experience for chatting, creating, learning, and exploring AI functionalities across a variety of devices. The application accommodates a selection of open models, such as Llama, Gemma, Qwen, and DeepSeek, allowing users to effortlessly switch between them and tailor outputs for different tasks. Functioning entirely offline, it removes the necessity for logins and ensures that no data is collected or transmitted, thus providing complete privacy and control over personal information. Users can interact with AI through natural conversations, evaluate documents or images, and generate text through a user-friendly interface designed for simplicity and responsiveness. This thoughtful design not only fosters creativity and exploration but also significantly enriches the overall user experience, making it an invaluable tool for anyone looking to engage with AI. Ultimately, Locally AI empowers users to take full advantage of AI technology while prioritizing their privacy and ease of use.
What is EmbeddingGemma?
EmbeddingGemma is a flexible multilingual text embedding model boasting 308 million parameters, engineered to be both lightweight and highly effective, which enables it to function effortlessly on everyday devices such as smartphones, laptops, and tablets. Built on the Gemma 3 architecture, this model supports over 100 languages and accommodates up to 2,000 input tokens, leveraging Matryoshka Representation Learning (MRL) to offer customizable embedding sizes of 768, 512, 256, or 128 dimensions, thereby achieving a balance between speed, storage, and accuracy. Its capabilities are enhanced by GPU and EdgeTPU acceleration, allowing it to produce embeddings in just milliseconds—taking less than 15 ms for 256 tokens on EdgeTPU—while its quantization-aware training keeps memory usage under 200 MB without compromising on quality. These features make it exceptionally well-suited for real-time, on-device applications, including semantic search, retrieval-augmented generation (RAG), classification, clustering, and similarity detection. The model's versatility extends to personal file searches, mobile chatbot functionalities, and specialized applications, with a strong emphasis on user privacy and operational efficiency. Therefore, EmbeddingGemma is not only effective but also adapts well to various contexts, solidifying its position as a premier choice for diverse text processing tasks in real time.
Integrations Supported
Gemma 4
Cogito
DeepSeek
Gemma
Gemma 3
Hugging Face
IBM Granite
Llama
Qwen
SmolLM2
Integrations Supported
Gemma 4
Cogito
DeepSeek
Gemma
Gemma 3
Hugging Face
IBM Granite
Llama
Qwen
SmolLM2
API Availability
Has API
API Availability
Has API
Pricing Information
Free
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Locally AI
Company Location
United States
Company Website
locallyai.app/
Company Facts
Organization Name
Date Founded
1998
Company Location
United States
Company Website
ai.google.dev/gemma/docs/embeddinggemma