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Average Ratings 0 Ratings
Description
Leanstral 1.5 is a model licensed under Apache-2.0, designed for effective proof engineering in Lean 4, aimed at enhancing the capabilities and accessibility of formal verification. It boasts a total of 119 billion parameters, with 6 billion of them being active, marking a significant improvement in performance for tasks such as theorem proving, agent-based proof engineering, and the verification of practical code. The development of Leanstral 1.5 involved a comprehensive three-stage training process, which included mid-training, supervised fine-tuning, and reinforcement learning utilizing CISPO. In a multiturn environment, the model is tasked with receiving a theorem statement, submitting a proof, and refining its approach based on feedback from the Lean compiler until the proof is either successfully compiled or the available resources are depleted. In the code agent setting, Leanstral functions similarly to a developer navigating a raw filesystem, allowing it to edit files, execute bash commands, and interact with the Lean language server to monitor goals, errors, and type information in real time. This innovative approach not only streamlines the proof engineering process but also significantly enhances the user experience in formal verification tasks.
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.
API Access
Has API
Yes
API Access
Has API
Yes
Integrations
Claude Code
No
Hermes Agent
No
Kilo Code
No
OpenClaw
No
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
$0.0028 per 1M tokens
Free Trial
No
Free Version
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
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
Mistral AI
Founded
2023
Country
France
Website
mistral.ai/news/leanstral-1-5/
Vendor Details
Company Name
Ant Group
Founded
2014
Country
China
Website
developer.ant-ling.com/en/docs/models/ring/