Muse Wonder Full
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What is SWE-1?
SWE-1 is an advanced family of software engineering models by Windsurf, designed to accelerate the software development lifecycle by addressing the full spectrum of engineering tasks. Unlike traditional models that focus solely on code, SWE-1 models—SWE-1, SWE-1-lite, and SWE-1-mini—are built with flow awareness, ensuring seamless collaboration between AI and users. By handling everything from terminal commands to user feedback and incomplete states, SWE-1 allows engineers to achieve higher productivity and deliver robust software solutions. With its groundbreaking approach, SWE-1 significantly enhances development speed and accuracy, providing a powerful tool for teams and individual developers alike.
What is Muse Wonder Full?
Muse Wonder Full is a large-scale artificial intelligence model developed by Meta for advanced agentic reasoning, professional knowledge work, and complex software engineering tasks. Introduced in October 2026, it represents the larger variant of the Muse Wonder family and builds on Meta's research into scaling pretrained models and reinforcement learning. The model is designed to manage complex objectives involving multiple steps, changing requirements, external information, and sustained problem-solving. Its Active Memory capability maintains important contextual information across conversations and retrieves relevant details when they become useful for subsequent tasks. Active Focus enables the model to pursue long-running assignments, explore alternative strategies, recover from obstacles, and adapt to new information. The system can request clarification when instructions are incomplete and seek user confirmation before performing important actions. Muse Wonder Full supports professional applications involving legal documents, financial analysis, health-related information, and business process automation. Its coding capabilities include generating software, analyzing existing repositories, tracking implementation requirements, modifying source code, and performing iterative testing and debugging. Meta trained the model on diverse long-running software engineering tasks to support development projects requiring multiple rounds of implementation and revision. Evaluations include MemoryBench for contextual memory, FocusBench for sustained task execution, SWE-Marathon and DeepSWE for software engineering, and additional assessments covering professional agents and unfamiliar problem-solving tasks. Muse Wonder Full is available to Muse Code subscribers, with Meta also reporting safety evaluations addressing personal information handling, adversarial instructions, unauthorized code execution, and misuse prevention.
Integrations Supported
Devin Desktop
AI Agents Directory
Integrations Supported
Devin Desktop
Bash
Dart
Go
Instagram
Kubernetes
LlamaIndex
Meta Model API
Muse
API Availability
API Availability
Has API
Pricing Information
Pricing not provided
Pricing Information
$50/month
Supported Platforms
SaaS
Supported Platforms
SaaS
Customer Service / Support
Web-Based Support
Customer Service / Support
Web-Based Support
Training Options
Documentation Hub
Training Options
Documentation Hub
Company Facts
Organization Name
Cognition
Date Founded
2023
Company Location
United States
Company Website
devin.ai/blog/windsurf-wave-9-swe-1
Company Facts
Organization Name
Meta
Date Founded
2004
Company Location
United States
Company Website
meta.ai/
Categories and Features
AI Coding Models
Not specified
AI Models
Not specified
Categories and Features
AI Coding Models
Not specified
AI Models
Not specified
AI Reasoning Models
Not specified
Foundation Models
Not specified
Large Language Models
Not specified
Multimodal Models
Not specified