Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
CompactifAI, developed by Multiverse Computing, is an innovative platform for compressing AI models that aims to enhance the speed, affordability, energy efficiency, and portability of advanced AI systems, including large language models, by significantly minimizing their size while maintaining performance levels. By leveraging cutting-edge quantum-inspired methodologies like tensor networks for the compression of foundational AI models, CompactifAI effectively reduces memory and storage needs, allowing these models to operate with diminished computational demands and be deployed in a variety of environments, from cloud and on-premises solutions to edge and mobile applications, through a managed API or private deployment options. This platform not only accelerates inference speed and reduces energy and hardware expenses but also supports privacy-conscious local execution and facilitates the creation of specialized, efficient AI models optimized for specific tasks, ultimately assisting teams in addressing the hardware limitations and sustainability issues commonly encountered in traditional AI implementations. Furthermore, by enabling more versatile deployment, CompactifAI empowers organizations to utilize advanced AI capabilities in a broader range of scenarios than ever before.
Description
The Ling 2.6 Flash represents the newest and most economical addition to the Ling series, utilizing a Mixture of Experts architecture that encompasses a total of 104 billion parameters, with 7.4 billion of those being actively engaged. This model is crafted to strike an ideal balance between inference speed and computational expense, making it an excellent fit for diverse scenarios where reasoning prowess, high throughput, and effective deployment are essential. By employing its MoE structure, Ling ensures that each token activates only the most pertinent expert subnetworks, significantly reducing the actual computational load while preserving the expansive capacity of the model. Offering a native context window of 256K, Ling 2.6 Flash is capable of handling around 200,000 characters of lengthy input, adeptly retrieving critical long-range information regardless of its position in the context. Furthermore, its overall benchmark performance rivals or surpasses that of 40 billion parameter Dense models, highlighting its competitive edge in the field of AI. This blend of efficiency and performance makes Ling 2.6 Flash a noteworthy option for developers seeking advanced capabilities without excessive resource demands.
API Access
Has API
Yes
API Access
Has API
Yes
Integrations
Amazon Web Services (AWS)
Yes
Claude Code
No
Hermes Agent
No
Kilo Code
No
Llama
Yes
Mistral AI
Yes
OpenClaw
No
OpenRouter
No
ZenMux
No
Integrations
Amazon Web Services (AWS)
No
Claude Code
Yes
Hermes Agent
Yes
Kilo Code
Yes
Llama
No
Mistral AI
No
OpenClaw
Yes
OpenRouter
Yes
ZenMux
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$0.00037 per 1M tokens
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Multiverse Computing
Founded
2019
Country
Basque Country
Website
multiversecomputing.com/compactifai
Vendor Details
Company Name
Ant Group
Founded
2014
Country
China
Website
developer.ant-ling.com/en/docs/models/ling/
Product Features
Artificial Intelligence
Chatbot
No
For Healthcare
No
For Sales
No
For eCommerce
No
Image Recognition
No
Machine Learning
No
Multi-Language
No
Natural Language Processing
No
Predictive Analytics
No
Process/Workflow Automation
No
Rules-Based Automation
No
Virtual Personal Assistant (VPA)
No