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What is LTM-2-mini?

LTM-2-mini is designed to manage a context of 100 million tokens, which is roughly equivalent to about 10 million lines of code or approximately 750 full-length novels. This model utilizes a sequence-dimension algorithm that proves to be around 1000 times more economical per decoded token compared to the attention mechanism employed by Llama 3.1 405B when operating within the same 100 million token context window. Additionally, the difference in memory requirements is even more pronounced; running Llama 3.1 405B with a 100 million token context requires an impressive 638 H100 GPUs per user just to sustain a single 100 million token key-value cache. In stark contrast, LTM-2-mini only needs a tiny fraction of the high-bandwidth memory available in one H100 GPU for the equivalent context, showcasing its remarkable efficiency. This significant advantage positions LTM-2-mini as an attractive choice for applications that require extensive context processing while minimizing resource usage. Moreover, the ability to efficiently handle such large contexts opens the door for innovative applications across various fields.

What is GPT-5 mini?

GPT-5 mini is a faster, more affordable variant of OpenAI’s advanced GPT-5 language model, specifically tailored for well-defined and precise tasks that benefit from high reasoning ability. It accepts both text and image inputs (image input only), and generates high-quality text outputs, supported by a large 400,000-token context window and a maximum of 128,000 tokens in output, enabling complex multi-step reasoning and detailed responses. The model excels in providing rapid response times, making it ideal for use cases where speed and efficiency are critical, such as chatbots, customer service, or real-time analytics. GPT-5 mini’s pricing structure significantly reduces costs, with input tokens priced at $0.25 per million and output tokens at $2 per million, offering a more economical option compared to the flagship GPT-5. While it supports advanced features like streaming, function calling, structured output generation, and fine-tuning, it does not currently support audio input or image generation capabilities. GPT-5 mini integrates seamlessly with multiple API endpoints including chat completions, responses, embeddings, and batch processing, providing versatility for a wide array of applications. Rate limits are tier-based, scaling from 500 requests per minute up to 30,000 per minute for higher tiers, accommodating small to large scale deployments. The model also supports snapshots to lock in performance and behavior, ensuring consistency across applications. GPT-5 mini is ideal for developers and businesses seeking a cost-effective solution with high reasoning power and fast throughput. It balances cutting-edge AI capabilities with efficiency, making it a practical choice for applications demanding speed, precision, and scalability.

Media

Media

Integrations Supported

Integrations Supported

Amarsia
Bash
Buda
C++
ChatGPT Plus
Codex CLI
Google Drive
HTML
JavaScript
Kotlin
Microsoft Foundry Models
OpenAI Codex
PHP
PrivatClaw
React
Shiori
Sup AI
TranslateAI
Transor

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

$0.25 per 1M tokens
Input: $0.25 per 1M tokens
Output: $2 per 1M tokens

Supported Platforms

SaaS

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac

Customer Service / Support

Not specified

Customer Service / Support

Web-Based Support

Training Options

Not specified

Training Options

Documentation Hub

Company Facts

Organization Name

Magic AI

Date Founded

2022

Company Location

United States

Company Website

magic.dev/

Company Facts

Organization Name

OpenAI

Date Founded

2015

Company Location

United States

Company Website

platform.openai.com/docs/models/gpt-5-mini

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Large Language Models

Not specified

Small Language Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Multimodal Models

Not specified

Small Language Models

Not specified

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