Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
The Gemini Embedding's inaugural text model, known as gemini-embedding-001, is now officially available through the Gemini API and Vertex AI, having maintained its leading position on the Massive Text Embedding Benchmark Multilingual leaderboard since its experimental introduction in March, attributed to its outstanding capabilities in retrieval, classification, and various embedding tasks, surpassing both traditional Google models and those from external companies. This highly adaptable model accommodates more than 100 languages and has a maximum input capacity of 2,048 tokens, utilizing the innovative Matryoshka Representation Learning (MRL) method, which allows developers to select output dimensions of 3072, 1536, or 768 to ensure the best balance of quality, performance, and storage efficiency. Developers are able to utilize it via the familiar embed_content endpoint in the Gemini API, and although the older experimental versions will be phased out by 2025, transitioning to the new model does not necessitate re-embedding of previously stored content. This seamless migration process is designed to enhance user experience without disrupting existing workflows.
Description
The newest version in the Llama series, Llama 3.3, represents a significant advancement in language models aimed at enhancing AI's capabilities in understanding and communication. It boasts improved contextual reasoning, superior language generation, and advanced fine-tuning features aimed at producing exceptionally accurate, human-like responses across a variety of uses. This iteration incorporates a more extensive training dataset, refined algorithms for deeper comprehension, and mitigated biases compared to earlier versions. Llama 3.3 stands out in applications including natural language understanding, creative writing, technical explanations, and multilingual interactions, making it a crucial asset for businesses, developers, and researchers alike. Additionally, its modular architecture facilitates customizable deployment in specific fields, ensuring it remains versatile and high-performing even in large-scale applications. With these enhancements, Llama 3.3 is poised to redefine the standards of AI language models.
API Access
Has API
API Access
Has API
Integrations
Python
1min.AI
AICamp
Azure AI Foundry Agent Service
BlueFlame AI
C
C++
CSS
CerebrasCoder
Clojure
Integrations
Python
1min.AI
AICamp
Azure AI Foundry Agent Service
BlueFlame AI
C
C++
CSS
CerebrasCoder
Clojure
Pricing Details
$0.15 per 1M input tokens
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
Founded
1998
Country
United States
Website
developers.googleblog.com/en/gemini-embedding-available-gemini-api/
Vendor Details
Company Name
Meta
Founded
2004
Country
United States
Website
www.llama.com/docs/model-cards-and-prompt-formats/llama3_3/