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Description

Magic’s LTM-1 technology facilitates context windows that are 50 times larger than those typically used in transformer models. As a result, Magic has developed a Large Language Model (LLM) that can effectively process vast amounts of contextual information when providing suggestions. This advancement allows our coding assistant to access and analyze your complete code repository. With the ability to reference extensive factual details and their own prior actions, larger context windows can significantly enhance the reliability and coherence of AI outputs. We are excited about the potential of this research to further improve user experience in coding assistance applications.

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 

Screenshots View All

Screenshots View All

Integrations

.NET No 
C No 
CSS No 
Codex CLI No 
HTML No 
Hermes Agent No 
Java No 
JavaScript No 
Kotlin No 
Kubernetes No 
Model Context Protocol (MCP) No 
Muse Code No 
Muse Image No 
Muse Spark No 
OpenAI Codex No 
OpenClaw No 
OpenCode No 
PHP No 
Ruby No 
XML No 

Integrations

.NET Yes 
C Yes 
CSS Yes 
Codex CLI Yes 
HTML Yes 
Hermes Agent Yes 
Java Yes 
JavaScript Yes 
Kotlin Yes 
Kubernetes Yes 
Model Context Protocol (MCP) Yes 
Muse Code Yes 
Muse Image Yes 
Muse Spark Yes 
OpenAI Codex Yes 
OpenClaw Yes 
OpenCode Yes 
PHP Yes 
Ruby Yes 
XML 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 Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
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 No 
Live Rep (24/7) No 
Online Support No 

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) No 
In Person No 

Vendor Details

Company Name

Magic AI

Founded

2022

Country

United States

Website

magic.dev/blog/ltm-1

Vendor Details

Company Name

Meta

Founded

2004

Country

United States

Website

meta.ai

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