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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

LTM-2-mini operates with a context of 100 million tokens, which is comparable to around 10 million lines of code or roughly 750 novels. This model employs a sequence-dimension algorithm that is approximately 1000 times more cost-effective per decoded token than the attention mechanism used in Llama 3.1 405B when handling a 100 million token context window. Furthermore, the disparity in memory usage is significantly greater; utilizing Llama 3.1 405B with a 100 million token context necessitates 638 H100 GPUs per user solely for maintaining a single 100 million token key-value cache. Conversely, LTM-2-mini requires only a minuscule portion of a single H100's high-bandwidth memory for the same context, demonstrating its efficiency. This substantial difference makes LTM-2-mini an appealing option for applications needing extensive context processing without the hefty resource demands.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Quickwork

Integrations

Quickwork

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Magic AI

Founded

2022

Country

United States

Website

magic.dev/blog/ltm-1

Vendor Details

Company Name

Magic AI

Founded

2022

Country

United States

Website

magic.dev/

Product Features

Product Features

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