Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
The Large-Scale Optimizer™ is a collaborative creation by Michael Best, who is a Professor Emeritus in the Department of Combinatorics and Optimization at the University of Waterloo, and Jivendra Kale, the President of Financiometrics Inc. This remarkable quadratic optimizer is designed for the swift construction of long-only, long-short, and market-neutral portfolios that can encompass thousands of assets, allowing for effective risk management in relation to a standard or benchmark portfolio. Additionally, it serves as a tool for asset allocation that employs Markowitz mean-variance analysis principles. This version of the Large-Scale Optimizer™ is an unrestricted edition that can be acquired either as an application or as a subroutine library that can be integrated into your software. Utilizing an advanced active set method, which has been further refined through the implementation of penalty function techniques, the Large-Scale Optimizer™ achieves significant speed enhancements to ensure the attainment of a true global optimal solution for extensive, real-world portfolio optimization challenges, even when variable transaction costs are present. This unique capability makes it an essential tool for financial analysts and portfolio managers seeking to optimize their investment strategies efficiently.
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
No
API Access
Has API
Yes
Integrations
Claude Code
No
Hermes Agent
No
Kilo Code
No
OpenClaw
No
OpenRouter
No
ZenMux
No
Integrations
Claude Code
Yes
Hermes Agent
Yes
Kilo Code
Yes
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
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
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
Yes
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
No
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Financiometrics
Website
www.financiometrics.com
Vendor Details
Company Name
Ant Group
Founded
2014
Country
China
Website
developer.ant-ling.com/en/docs/models/ling/
Product Features
Financial Risk Management
Compliance Management
No
Credit Risk Management
No
For Hedge Funds
Yes
Liquidity Analysis
No
Loan Portfolio Management
No
Market Risk Management
No
Operational Risk Management
No
Portfolio Management
Yes
Portfolio Modeling
No
Risk Analytics Benchmarks
No
Stress Tests
No
Value At Risk Calculation
No