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Average Ratings 0 Ratings

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features
design
support

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Write a Review

Description

Kimi K2.6 is an advanced agentic AI model created by Moonshot AI, aiming to enhance practical implementation, programming, and complex reasoning compared to its predecessors, K2 and K2.5. This model is based on a Mixture-of-Experts framework and the multimodal, agent-centric principles of the Kimi series, merging language comprehension, coding capabilities, and tool utilization into one cohesive system that can plan and execute intricate workflows. It features enhanced reasoning skills and significantly better agent planning, enabling it to deconstruct tasks, synchronize various tools, and tackle multi-file or multi-step challenges with increased precision and effectiveness. Additionally, it provides robust tool-calling capabilities with a high degree of reliability, facilitating seamless integration with external platforms like web searches or APIs, and incorporates built-in validation systems to guarantee the accuracy of execution formats. Notably, Kimi K2.6 represents a significant leap forward in the realm of AI, setting new standards for the complexity and reliability of automated tasks.

Description

TimesFM-3 represents an advanced time series foundation model that excels in highly precise multivariate forecasting with a single forward pass. This model, which consists of 330 million parameters, has undergone pre-training on a vast corpus of real-world and synthetic time series data, totaling over 1 trillion time points, thereby enhancing the effectiveness and zero-shot generalization capabilities seen in previous TimesFM iterations. It is adept at simultaneously predicting numerous coevolving time series and understanding dependencies that bolster accuracy without the need for task-specific fine-tuning. Furthermore, it accommodates multiple forecasting targets, including both point and quantile predictions, and incorporates past covariates that are only available historically, alongside dynamic covariates that pertain to future events such as planned promotions, holidays, or weather changes. Utilizing a decoder-only transformer architecture, TimesFM-3 processes sequential data in segments of 32 time steps, employing alternating causal temporal attention and full variate attention to integrate patterns across both time and interrelated series effectively. As a result, it provides a robust tool for forecasting complex time-dependent phenomena in various applications.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

AiAssistWorks Yes 
Alibaba AI Coding Plan Yes 
C# Yes 
Cerebras Yes 
Claw Code Yes 
Cline Yes 
Factory Droid Yes 
Go Yes 
Java Yes 
JavaScript Yes 
JetBrains Junie Yes 
Kimi Code Yes 
Novita AI Yes 
Odysseus Yes 
Ollama Yes 
Rust Yes 
Shiori Yes 
Tabbit Browser Yes 
Vercel AI Gateway Yes 
ZooClaw Yes 

Integrations

AiAssistWorks No 
Alibaba AI Coding Plan No 
C# No 
Cerebras No 
Claw Code No 
Cline No 
Factory Droid No 
Go No 
Java No 
JavaScript No 
JetBrains Junie No 
Kimi Code No 
Novita AI No 
Odysseus No 
Ollama No 
Rust No 
Shiori No 
Tabbit Browser No 
Vercel AI Gateway No 
ZooClaw No 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
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) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Moonshot AI

Founded

2023

Country

China

Website

www.kimi.com/blog/kimi-k2-6

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

research.google/blog/timesfm-3-a-zero-shot-foundation-model-for-multivariate-forecasting/

Product Features

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