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What is Reka?

Our sophisticated multimodal assistant has been thoughtfully designed with an emphasis on privacy, security, and operational efficiency. Yasa is equipped to analyze a range of content types, such as text, images, videos, and tables, with ambitions to broaden its capabilities in the future. It serves as a valuable resource for generating ideas for creative endeavors, addressing basic inquiries, and extracting meaningful insights from your proprietary data. With only a few simple commands, you can create, train, compress, or implement it on your own infrastructure. Our unique algorithms allow for customization of the model to suit your individual data and needs. We employ cutting-edge methods that include retrieval, fine-tuning, self-supervised instruction tuning, and reinforcement learning to enhance our model, ensuring it aligns effectively with your specific operational demands. This approach not only improves user satisfaction but also fosters productivity and innovation in a rapidly evolving landscape. As we continue to refine our technology, we remain committed to providing solutions that empower users to achieve their goals.

What is GPT-5 nano?

GPT-5 nano is OpenAI’s fastest and most cost-efficient version of the GPT-5 model, engineered to handle high-speed text and image input processing for tasks such as summarization, classification, and content generation. It features an extensive 400,000-token context window and can output up to 128,000 tokens, allowing for complex, multi-step language understanding despite its focus on speed. With ultra-low pricing—$0.05 per million input tokens and $0.40 per million output tokens—GPT-5 nano makes advanced AI accessible to budget-conscious users and developers working at scale. The model supports a variety of advanced API features, including streaming output, function calling for interactive applications, structured outputs for precise control, and fine-tuning for customization. While it lacks support for audio input and web search, GPT-5 nano supports image input, code interpretation, and file search, broadening its utility. Developers benefit from tiered rate limits that scale from 500 to 30,000 requests per minute and up to 180 million tokens per minute, supporting everything from small projects to enterprise workloads. The model also offers snapshots to lock performance and behavior, ensuring consistent results over time. GPT-5 nano strikes a practical balance between speed, cost, and capability, making it ideal for fast, efficient AI implementations where rapid turnaround and budget are critical. It fits well for applications requiring real-time summarization, classification, chatbots, or lightweight natural language processing tasks. Overall, GPT-5 nano expands the accessibility of OpenAI’s powerful AI technology to a broader user base.

Media

Media

Integrations Supported

Bash
C++
CSS
ChatGPT
ChatGPT Pro
Codex CLI
Ghost
GitHub
Go
Google Drive
HTML
Java
Microsoft SharePoint
PowerShell
Python
React
Rust
SQL
TypeScript

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

$0.05 per 1M tokens
Input: $0.05 per 1M tokens
Output: $0.4 per 1M tokens

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Not specified

Training Options

Documentation Hub

Company Facts

Organization Name

Reka

Company Location

United States

Company Website

reka.ai/

Company Facts

Organization Name

OpenAI

Date Founded

2015

Company Location

United States

Company Website

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

Categories and Features

AI Models

Not specified

AI Tools

Not specified

Large Language Models

Not specified

LLM API

Not specified

Multimodal Models

Not specified

Categories and Features

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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