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Samsung Exynos System-on-Chips

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Description

Samsung's in-house developed Exynos system-on-chips designed to compete with Qualcomm Snapdragon processors in flagship devices

Market positioning

Developing competitive alternative to reduce Qualcomm dependency

Target audience

Samsung's Galaxy flagship smartphone series and other mobile devices

Use cases

High-performance system-on-chip for flagship smartphones and mobile devices, enabling Samsung to reduce reliance on third-party processors

Company information

Company size

Large Enterprise (290,000+ employees)

Revenue

$244 billion (2023)

Scale

Global

Number of users

Internal Samsung product lines

Features

2nm GAA process technology, Designed for flagship smartphone performance, Integration with Samsung's manufacturing capabilities, Volume production planned for second half of 2025

Pricing

Pricing modelInternal development and manufacturing
Starting priceInternal cost structure - not publicly available
Billing periodN/A - Internal use

Rating

Pros and cons

Based on: (AI summary)

Pros

  • Advanced 2nm manufacturing process
  • Vertical integration with Samsung's fab capabilities
  • Cost control through internal production
  • Planned reintegration into flagship models by 2026

Cons

  • Historical struggles with flagship device integration
  • Performance gaps compared to Qualcomm Snapdragon
  • Still relying on Qualcomm for Galaxy S25 series in 2025

Feature Comparison

Top features across 8 competitors (most common first)

Feature Samsung Exy…A18 with iO…Kinaxis Rap…Dimensity 9…Apple Baseb…Tensor G3 a…Exynos 2400MediaTek Sm…
Generative AI capabilities
5G connectivity
Advanced manufacturing process
2nm GAA process technology
Designed for flagship smartphone performance
Volume production planned for second half of 2025
Dedicated neural processors
Image and video generation
iOS 18 integration
On-device LLM support
Personal assistance AI
Real-time translation
Concurrent supply chain planning
High integrity execution
Sales and operations planning (S&OP)
Supply chain disruption management
What-if scenario modeling
Cost-effective AI implementation
Generative AI support
On-device neural processing