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Description
ERNIE 5.1 is Baidu’s next-generation large language model engineered to provide advanced reasoning, autonomous agent capabilities, creative writing performance, and enterprise-grade AI intelligence with highly optimized efficiency. Built on the pre-training foundation of ERNIE 5.0, the model significantly reduces parameter size and computational requirements while still delivering leading performance across major international AI benchmarks. ERNIE 5.1 demonstrates strong capabilities in reasoning, mathematical problem solving, knowledge retrieval, search tasks, and agentic workflows that allow it to handle complex multi-step operations and decision-making scenarios. The platform introduces a fully asynchronous reinforcement learning architecture designed to improve scalability, training efficiency, resource utilization, and long-horizon task stability for large-scale AI development. Baidu also implemented a multi-stage reinforcement learning pipeline that separates expert capability training from unified capability fusion, allowing the model to specialize in areas such as coding, reasoning, search, and conversational intelligence without creating performance conflicts between domains. ERNIE 5.1 supports advanced creative generation with improved emotional understanding, narrative structure control, stylistic adaptability, and contextual awareness for writing-intensive applications. The model performs competitively against leading closed-source global AI systems in knowledge benchmarks, reasoning evaluations, and creative content generation tasks. ERNIE 5.1 is also integrated into creative production platforms, AI storytelling systems, roleplay applications, and agentic AI environments that support content creators and enterprise workflows.
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.
API Access
Has API
API Access
Has API
Integrations
C
C#
C++
CSS
Clojure
ERNIE Bot
Elixir
F#
Go
HTML
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
Free
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Baidu
Founded
2000
Country
China
Website
ernie.baidu.com
Vendor Details
Company Name
Mistral AI
Founded
2023
Country
France
Website
mistral.ai/news/leanstral-1-5/