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features
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support

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Description

Ring is a sophisticated trillion-parameter thinking model created by Ant Group, specifically tailored for real-world Agent workflows. It employs a Mixture of Experts architecture similar to that of Ling, activating approximately 63 billion parameters during each inference, and is particularly geared towards tasks such as coding agents, utilizing tools, collaborating with multiple tools, engineering development, conducting research analysis, and executing long-term tasks. Instead of merely striving for "smarter" outcomes, Ring prioritizes the reliable completion of intricate tasks while maintaining a cost-effective approach, effectively balancing quality, speed, and efficiency in production settings. The latest iteration, Ring-2.6-1T, incorporates an adjustable Reasoning Effort mechanism that features high and xhigh reasoning intensity levels, which allocates an adaptive reasoning budget according to the complexity of the task at hand. The high mode is specifically optimized for high-frequency Agent workflows, resulting in lower token costs and quicker multi-step execution, while also facilitating multi-turn interactions, tool collaboration, and task decomposition. As a result, Ring demonstrates a significant advancement in enhancing the capabilities of agents in various operational contexts.

Description

Trinity Large Thinking is an innovative open-source reasoning model crafted by Arcee AI, tailored for intricate, multi-step problem solving and workflows involving autonomous agents that necessitate extended planning and the use of various tools. This model features a sparse Mixture-of-Experts architecture, boasting a remarkable total of around 400 billion parameters, with approximately 13 billion being active for each token, which enhances its efficiency while ensuring robust reasoning capabilities across a range of tasks, including mathematical calculations, code generation, and comprehensive analysis. A notable advancement in this model is its ability to perform extended chain-of-thought reasoning, which allows it to produce intermediate "thinking traces" prior to delivering final solutions, thereby boosting accuracy and reliability in complex situations. Furthermore, Trinity Large Thinking accommodates a substantial context window of up to 262K tokens, allowing it to effectively process lengthy documents, retain context during prolonged interactions, and function seamlessly in continuous agent loops. This model's design reflects a commitment to pushing the boundaries of what automated reasoning systems can achieve.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

OpenClaw Yes 
Claude Code Yes 
Claude Fable 5 No 
Claude Fable 5.1 No 
Claude Fable 5.5 No 
Claude Haiku 5.5 No 
Claude Mythos 5 No 
Claude Mythos 5.1 No 
Claude Opus 4.6 No 
Claude Opus 4.7 No 
Claude Opus 4.8 No 
Claude Opus 5 No 
Claude Opus 5.5 No 
Claude Sonnet 5.5 No 
Hermes Agent Yes 
Kilo Code Yes 
OpenRouter No 
Vercel AI Gateway No 
Visual Studio Code No 

Integrations

OpenClaw Yes 
Claude Code No 
Claude Fable 5 Yes 
Claude Fable 5.1 Yes 
Claude Fable 5.5 Yes 
Claude Haiku 5.5 Yes 
Claude Mythos 5 Yes 
Claude Mythos 5.1 Yes 
Claude Opus 4.6 Yes 
Claude Opus 4.7 Yes 
Claude Opus 4.8 Yes 
Claude Opus 5 Yes 
Claude Opus 5.5 Yes 
Claude Sonnet 5.5 Yes 
Hermes Agent No 
Kilo Code No 
OpenRouter Yes 
Vercel AI Gateway Yes 
Visual Studio Code Yes 

Pricing Details

$0.0028 per 1M tokens
Free Trial No 
Free Version No 

Pricing Details

Free
Free Trial Yes 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
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) No 
In Person No 

Types of Training

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

Vendor Details

Company Name

Ant Group

Founded

2014

Country

China

Website

developer.ant-ling.com/en/docs/models/ring/

Vendor Details

Company Name

Arcee AI

Founded

2023

Country

United States

Website

www.arcee.ai/blog/trinity-large-thinking

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