Microsoft for Startups Founders
AWS Activate Startup
IBM Business Partner
Edge Impulse Experts Network
Intel Software Innovators
Google cloud Startup
Supported by Business Wales
Supported by Enterprise Hub
AI Model

Amazon Titan Embeddings G1 – Text v1.2

Amazon Titan Embeddings G1 – Text v1.2 is a powerful embedding model designed for high-performance text retrieval and other advanced tasks. It handles up to 8,000 tokens and produces vectors of 1,536 dimensions. Optimized for text retrieval, semantic similarity, and clustering, it supports over 25 languages and is capable of managing long documents effectively.

Context Window 8,000 tokens
TPM 300,000
RPM 2,000
Embedding Size 1,536

Amazon Titan Embeddings G1 – Text v1.2 is an advanced embedding model designed to excel in various text-based tasks with high performance and precision. Capable of processing up to 8,000 tokens and generating vectors of 1,536 dimensions, this model is tailored for text retrieval applications, offering enhanced capabilities for semantic similarity and clustering. Its robust architecture allows it to effectively handle long documents, though it is advisable to segment documents into logical parts, such as paragraphs or sections, for optimal retrieval performance.

Supporting over 25 languages, Titan Embeddings G1 – Text v1.2 is well-suited for diverse linguistic applications and global data analysis. The model’s high dimensional vector output and ability to manage extensive token inputs make it a versatile tool for complex text processing needs. It is particularly useful for organizations and developers seeking advanced solutions for text retrieval, semantic analysis, and clustering tasks across a range of languages and document types.

Supported Formats:

  • Text Retrieval
  • Semantic Similarity
  • Clustering

Amazon Titan Embeddings G1 – Text v1.2 represents a powerful choice for high-performance text embedding needs, offering comprehensive capabilities and extensive language support for advanced text-based applications.

CogniTech AI Credits

Below you will find all supported platforms and the related CogniTech AI Credits costs.

AWS Bedrock Credits

Details Input Credits Output Credits Fine-Tuning
Details Input Credits Output Credits Fine-Tuning
Version: All
Region: us-west-2
Context: 8,192
TPM: 300,000
RPM: 2,000
Chat: 0.013 / 1000 tokens
Chat: 0 / 1000 tokens
NA
6LfEEZcpAAAAAC84WZ_GBX2qO6dYAEXameYWeTpF