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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

MiMo-V2-Flash is a large language model created by Xiaomi that utilizes a Mixture-of-Experts (MoE) framework, combining remarkable performance with efficient inference capabilities. With a total of 309 billion parameters, it activates just 15 billion parameters during each inference, allowing it to effectively balance reasoning quality and computational efficiency. This model is well-suited for handling lengthy contexts, making it ideal for tasks such as long-document comprehension, code generation, and multi-step workflows. Its hybrid attention mechanism integrates both sliding-window and global attention layers, which helps to minimize memory consumption while preserving the ability to understand long-range dependencies. Additionally, the Multi-Token Prediction (MTP) design enhances inference speed by enabling the simultaneous processing of batches of tokens. MiMo-V2-Flash boasts impressive generation rates of up to approximately 150 tokens per second and is specifically optimized for applications that demand continuous reasoning and multi-turn interactions. The innovative architecture of this model reflects a significant advancement in the field of language processing.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Claude Code
Hugging Face
Xiaomi MiMo
Xiaomi MiMo Studio

Integrations

Claude Code
Hugging Face
Xiaomi MiMo
Xiaomi MiMo Studio

Pricing Details

Free
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

Mistral AI

Founded

2023

Country

France

Website

mistral.ai/news/leanstral-1-5/

Vendor Details

Company Name

Xiaomi Technology

Founded

2010

Country

China

Website

mimo.xiaomi.com/blog/mimo-v2-flash

Product Features

Product Features

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