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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.

Description

Introducing the next iteration of our open-source large language model, this version features model weights along with initial code for the pretrained and fine-tuned Llama language models, which span from 7 billion to 70 billion parameters. The Llama 2 pretrained models have been developed using an impressive 2 trillion tokens and offer double the context length compared to their predecessor, Llama 1. Furthermore, the fine-tuned models have been enhanced through the analysis of over 1 million human annotations. Llama 2 demonstrates superior performance against various other open-source language models across multiple external benchmarks, excelling in areas such as reasoning, coding capabilities, proficiency, and knowledge assessments. For its training, Llama 2 utilized publicly accessible online data sources, while the fine-tuned variant, Llama-2-chat, incorporates publicly available instruction datasets along with the aforementioned extensive human annotations. Our initiative enjoys strong support from a diverse array of global stakeholders who are enthusiastic about our open approach to AI, including companies that have provided valuable early feedback and are eager to collaborate using Llama 2. The excitement surrounding Llama 2 signifies a pivotal shift in how AI can be developed and utilized collectively.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

1min.AI No 
AI-FLOW No 
AI/ML API No 
Amazon Bedrock No 
Automi No 
Batteries Included No 
BrandRank.AI No 
Cyte No 
Ema No 
Evertune No 
GaiaNet No 
Gopher No 
Groq No 
Kiin No 
Meta AI No 
OpenPipe No 
Second State No 
Solar Mini No 
Taylor AI No 
WebLLM No 

Integrations

1min.AI Yes 
AI-FLOW Yes 
AI/ML API Yes 
Amazon Bedrock Yes 
Automi Yes 
Batteries Included Yes 
BrandRank.AI Yes 
Cyte Yes 
Ema Yes 
Evertune Yes 
GaiaNet Yes 
Gopher Yes 
Groq Yes 
Kiin Yes 
Meta AI Yes 
OpenPipe Yes 
Second State Yes 
Solar Mini Yes 
Taylor AI Yes 
WebLLM Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
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 No 

Types of Training

Training Docs No 
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/

Vendor Details

Company Name

Meta

Founded

2004

Country

United States

Website

ai.meta.com/llama/

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