Latest

ATOM™ demonstration

ATOM™ demonstrates its energy efficiency against a GPU. Read about how ATOM™’s architecture enables its remarkable performance in our latest white paper:

Latest

Rebellions, a Trailblazing South Korean AI Chipmaker, Secures $15 Million Series B Extension Funding from Wa’ed Ventures, Saudi Aramco’s $500 Million Venture Capital Fund

The funding round marks the venture capital’s first investment activity in South Korea. Rebellions plans to accelerate AI chip development worldwide, utilizing the funds to expand its business into Saudi Arabia.

Latest

Rebellions paper has been accepted at ISSCC 2024

Our co-founder and CTO, Dr. Jinwook Oh, has successfully presented a paper along with our real-time demonstration.

Latest

Product Roadmap

Get ready to embark on a journey that will reshape the future and inspire change. Stay tuned for the grand reveal.

Latest

Korean AI chipmaker Rebellions Closes $124M Series B Fundraise

Securing a $124M Investment Amidst Startup Winter, Rebellions Achieves more than $200M in Total Funding, the Largest Among Semiconductor Startups in South Korea

  • System Solutions

    Start Lean, Scale Green

    Modular Framework for Scalable PODs

  • ATOM™

    5nm Versatile Inference SoC

    Versatile yet Energy Efficient
    AI System-on-Chip

  • ION™

    Scalable AI Compute Core

    Compute Granule with Maximum Flexibility and Efficiency

  • ATOM™

    5nm Versatile Inference SoC

    Versatile yet Energy Efficient

  • ION™

    AI Compute Core NPU

    Compute granule that brings
    maximum flexibility and energy efficiency

Featured models

SDK Video Tutorial

Video Tutorial l English
ATOM™ SDK User Guide
Video Tutorial l Japanese
ATOM™ SDK ユーザーガイド
Video Tutorial l Korean
ATOM™ SDK 사용 가이드
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Up next

TechBytes

How We are using Synopsys Solutions to Develop Our Next-Gen AI Chips
Rebellions and Samsung Electronics Partner to Target the Emerging Generative AI Market with Next-Generation AI Chip Co-Development
White Paper
White Paper: ATOM™ Architecture
See PDF
ISSCC 2024
ATOMUS: A 5nm 32 TFLOPS/128 TOPS ML System-on-Chip for Latency Critical Applications
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