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features
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support

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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

Qwen3-Coder is a versatile coding model that comes in various sizes, prominently featuring the 480B-parameter Mixture-of-Experts version with 35B active parameters, which naturally accommodates 256K-token contexts that can be extended to 1M tokens. This model achieves impressive performance that rivals Claude Sonnet 4, having undergone pre-training on 7.5 trillion tokens, with 70% of that being code, and utilizing synthetic data refined through Qwen2.5-Coder to enhance both coding skills and overall capabilities. Furthermore, the model benefits from post-training techniques that leverage extensive, execution-guided reinforcement learning, which facilitates the generation of diverse test cases across 20,000 parallel environments, thereby excelling in multi-turn software engineering tasks such as SWE-Bench Verified without needing test-time scaling. In addition to the model itself, the open-source Qwen Code CLI, derived from Gemini Code, empowers users to deploy Qwen3-Coder in dynamic workflows with tailored prompts and function calling protocols, while also offering smooth integration with Node.js, OpenAI SDKs, and environment variables. This comprehensive ecosystem supports developers in optimizing their coding projects effectively and efficiently.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Alibaba Cloud No 
Brokk No 
Gemini No 
Gemini Enterprise No 
Nebius Token Factory No 
NexaSDK No 
Node.js No 
Okara No 
OpenAI No 
OpenClaw No 
OpenCode No 
Oxlo.ai No 
Qwen2.5 No 
Shiori No 
SiliconFlow No 
Tinfoil No 
Together AI No 

Integrations

Alibaba Cloud Yes 
Brokk Yes 
Gemini Yes 
Gemini Enterprise Yes 
Nebius Token Factory Yes 
NexaSDK Yes 
Node.js Yes 
Okara Yes 
OpenAI Yes 
OpenClaw Yes 
OpenCode Yes 
Oxlo.ai Yes 
Qwen2.5 Yes 
Shiori Yes 
SiliconFlow Yes 
Tinfoil Yes 
Together AI Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

Free
Free Trial No 
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 No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
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) Yes 
In Person No 

Vendor Details

Company Name

Mistral AI

Founded

2023

Country

France

Website

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

Vendor Details

Company Name

Qwen

Founded

2023

Country

China

Website

qwenlm.github.io/blog/qwen3-coder/

Product Features

Product Features

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