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Description
MuSES achieves unparalleled accuracy in electro-optic and infrared renderings through a systematic process that starts with the identification of heat sources like engines, exhaust systems, bearings, and electronic components, followed by a comprehensive in-band diffuse radiosity solution. After establishing your sensor at a specified range, you can render multi-bounce radiance values that have been spectrally summed, utilizing DeltaT-RSS contrast metrics for detailed analysis. If you have a sensor response curve available, simply import it to uncover insights you may have overlooked. With MuSES, you can explore reality in unprecedented detail. The software’s capability extends to comprehensively address physics from heat sources to environmental influences, enabling you to effectively manage thermal signature contrasts and assess control kits essential for low observable design in any geographical context. You can rigorously evaluate heat shields, cooling methods, and camouflage surface treatments for in-band radiance while accounting for atmospheric attenuation along the sensor’s line-of-sight. By prioritizing engineering tasks with MuSES early in your project development cycle, you empower your team to make informed decisions that enhance overall design effectiveness. This foresight can significantly streamline the development process and improve project outcomes.
Description
Muse Spark 1.2 is Meta’s newest coding-focused model, released alongside Muse Code as part of Meta’s AI developer platform. The model improves on Muse Spark 1.1 with stronger code generation, complex debugging, codebase understanding, and full developer workflow performance. Muse Spark 1.2 powers Muse Code, a terminal coding agent that can plan changes, write code, validate results, and coordinate persistent background subagents. The model was co-trained with Muse Code so it performs well inside the agentic coding runtime and tool environment. Its training included scaled coding compute, broader training environment diversity, rejection-sampled harness trajectories, recipe optimizations, and Muse Code toolset integration. Muse Spark 1.2 is designed for long-horizon coding tasks such as whole-repository generation, large end-to-end projects, auto-research, and extended optimization work. It uses planning to sequence work, goal conditioning to stay aligned with the user’s objective, and context compaction to preserve useful knowledge over long sessions. The model also benefits from a self-improvement loop where Muse Spark 1.1 generated challenging coding environments and instruction-following templates for training. By combining coding specialization, agentic workflow support, long-horizon training, subagent compatibility, and Meta Model API availability, Muse Spark 1.2 helps developers build, debug, and optimize software more effectively.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Continue
No
Facebook
No
Gray Swan
No
Hermes Agent
No
Instagram
No
JavaScript
No
Meta Model API
No
Objective-C
No
Odysseus
No
OpenAI Codex
No
Integrations
Continue
Yes
Facebook
Yes
Gray Swan
Yes
Hermes Agent
Yes
Instagram
Yes
JavaScript
Yes
Meta Model API
Yes
Objective-C
Yes
Odysseus
Yes
OpenAI Codex
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$1.25 per 1M tokens (input)
$1.25 per million tokens in input, and $4.25 per million tokens of output
Free Trial
Yes
Free Version
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
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
Yes
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
Yes
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
ThermoAnalytics
Founded
1996
Country
United States
Website
www.thermoanalytics.com/muses
Vendor Details
Company Name
Meta
Founded
2004
Country
United States
Website
meta.ai
Product Features
Simulation
1D Simulation
No
3D Modeling
No
3D Simulation
No
Agent-Based Modeling
No
Continuous Modeling
No
Design Analysis
No
Direct Manipulation
No
Discrete Event Modeling
No
Dynamic Modeling
No
Graphical Modeling
No
Industry Specific Database
No
Monte Carlo Simulation
No
Motion Modeling
No
Presentation Tools
No
Stochastic Modeling
No
Turbulence Modeling
No
