Reka AI
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Reka AI

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Tool type: Productivity
Multimodal intelligence that understands and reasons with text, images, video, and audio.

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Reka AI

Reka AI is a cutting-edge multimodal AI platform designed to seamlessly process and analyze multiple forms of data, such as text, images, videos, audio, and code. Developed by a team of former DeepMind and Meta FAIR scientists, it combines state-of-the-art reasoning models with flexible deployment options to serve developers, enterprises, and researchers. Its advanced AI solutions include visual intelligence for video editing and search, as well as sophisticated web agents that can research complex questions by synthesizing information from multiple sources in natural language, enabling fast and accurate answers that typically take humans hours to produce. Reka balances transparency, performance, and real-world utility, making AI’s potential accessible across industries.

Key Features

  • Multimodal understanding: Processes and reasons across text, image, audio, and video data, enabling comprehensive content analysis and interaction.

  • State-of-the-art reasoning: Uses models like Flash 3.1 and Core 67B for deep, multi-hop reasoning that can browse the web and documents to answer complex queries.

  • Flexible deployment: Supports cloud, on-premises, and edge device integration, adaptable for startups and large enterprises alike.

  • Open-source and transparent: Offers downloadable models, evaluation tools, and code, promoting trust and community-driven development.

Use Cases

  • Researching and summarizing complex questions quickly, with data synthesized from multiple online and private sources.

  • Video and image content search, editing, and event detection for media, surveillance, or creative industries.

  • Building AI agents that require deep multimodal understanding and flexible deployment on varied platforms.

Technical Specifications

  • Offers multiple AI models spanning from ultra-compact Spark (1B parameters) to powerful Core (67B parameters) for varied computational needs.

  • Supports integration via Python SDK and HTTP API for easy and scalable application development.

  • Utilizes a 128K token context window (in Core) for large information processing and maintains high accuracy in language and math reasoning.

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