Beam

Beam

Reflection
+
+

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About

Beam is Reflection’s first open-weight model, a sparse Mixture-of-Experts model with 501 billion total parameters and 23 billion active parameters, built for coding, reasoning, and agentic workloads. Its capabilities come from large-scale pretraining and reinforcement learning, including training on 23.8 trillion diverse, curated, high-quality tokens from the web, public sources, and proprietary licensed datasets. Beam was trained with a particular focus on coding and agentic performance and is designed to deliver competitive open-weight capabilities with efficient inference compute. It supports complex software engineering, terminal, STEM, web search, tool-use, and general knowledge tasks, with reinforcement learning designed to improve multi-step reasoning, tool use, and adaptation to environment feedback. Users can control the tradeoff between performance and token usage through a reasoning effort parameter.

About

Muse Wonder is a frontier artificial intelligence model developed by Meta for personal assistance, professional workflows, software development, and autonomous agent tasks. The model combines Active Memory, which retrieves relevant information from previous conversations, with Active Focus, which supports sustained execution of complex, multistep assignments. Muse Wonder can assist with research, document analysis, financial and legal information, software engineering, and business process automation. Its agentic capabilities enable it to work across applications, use contextual information, adapt to obstacles, and request clarification or approval when necessary. The model supports coding activities ranging from small application development to complex software projects involving repeated testing and revision. Muse Wonder is available through the Meta Model API and Muse Code, with additional integration into Meta's Muse assistant planned for future releases.

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Developers, AI researchers, and engineering teams requiring a tool to run coding, reasoning, tool-use, and agentic workloads with an efficient open-weight language model

Audience

Software developers, AI engineers, researchers, business professionals, knowledge workers, enterprise teams, and individuals seeking advanced AI assistance for complex reasoning, software development, personalized workflows, and autonomous task execution

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Not Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Pricing

$4 per 1M tokens (input)
Input: $4 per 1M tokens
Output: $20 per 1M tokens
Free Version Not Supported
Free Trial Not Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

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Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5

Pros & Cons from Real Users

Pros

  • It feels much better at keeping track of what I am trying to accomplish across longer coding, research, and agent workflows instead of slowly losing the thread. Active Memory is especially useful. The model does a better job carrying important context forward, which makes extended projects feel less like repeatedly briefing a new assistant. I also like the new Active Focus approach. Wonder feels more deliberate about working toward the actual goal instead of getting distracted by side issues, which matters a lot when I give an agent something that takes many steps to finish. The coding ability is strong too. Meta is positioning Wonder against models like GPT-6 Astra and Claude Opus 5.5, and early reporting says it is especially competitive in software development and professional agentic work.

Cons

  • No real cons so far. I am still not sure how efficient pricing is.

Training

Documentation Supported
Webinars Not Supported
Live Online Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

Reflection
United States
reflection.ai/blog/introducing-beam

Company Information

Meta
Founded: 2004
United States
meta.ai/

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Categories

Categories

AI Coding Models Supported
AI Models Supported
Foundation Models Supported
Multimodal Models Supported

Integrations

C# Not Supported
Claude Code Not Supported
Cline Not Supported
Codex CLI Not Supported
Dart Not Supported
Devin Not Supported
Devin Desktop Not Supported
Instagram Not Supported
Kotlin Not Supported
LangChain Not Supported
Meta AI Not Supported
Meta Model API Not Supported
Muse Spark Not Supported
Objective-C Not Supported
OpenRouter Not Supported
PHP Not Supported
Python Not Supported
Rust Not Supported
Scala Not Supported
Swift Not Supported

Integrations

C# Supported
Claude Code Supported
Cline Supported
Codex CLI Supported
Dart Supported
Devin Supported
Devin Desktop Supported
Instagram Supported
Kotlin Supported
LangChain Supported
Meta AI Supported
Meta Model API Supported
Muse Spark Supported
Objective-C Supported
OpenRouter Supported
PHP Supported
Python Supported
Rust Supported
Scala Supported
Swift Supported
Claim Beam and update features and information
Claim Beam and update features and information
Claim Muse Wonder and update features and information
Claim Muse Wonder and update features and information