DEEPX
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About
DEEPX is an AI semiconductor company specializing in high-efficiency AI processors and systems designed for edge computing environments. Unlike traditional GPGPUs that consume significant power, DEEPX’s hardware, such as the DX-M1 and DX-H1 series, is engineered to provide high-speed inference for artificial intelligence models directly on local devices. This approach eliminates the need for constant cloud connectivity, which is often a bottleneck in remote or security-sensitive locations, reducing latency and bandwidth costs while significantly enhancing data privacy. The core of the technology lies in its proprietary NPU architecture and the DEEPX IQ8 quantization technique. This software-hardware synergy allows the chips to perform INT8 operations with the precision of FP32, maintaining high accuracy even for complex computer vision and LLM tasks. The DX-M1 module, for instance, consumes only 5W while outperforming a 40W GPU by up to 240%, leading to a significant reduction in Total Cost of Ownership. This efficiency translates to a claimed 94% saving in electricity costs over a five-year lifecycle compared to equivalent GPU-based systems. The tool suite is primarily aimed at manufacturers and developers working in smart mobility, industrial automation, and surveillance. Specifically, it serves engineers who need to deploy AI in power-constrained environments like smart factories or autonomous vehicles. By providing a comprehensive DXNN SDK, DEEPX allows developers to seamlessly port and optimize their existing AI models trained in standard frameworks onto the specialized DEEPX hardware. The product lineup includes various form factors, from standalone chips to M.2 modules and full AI workstations, ensuring compatibility with diverse system architectures. What sets DEEPX apart is its focus on "Physical AI" and sustainable energy usage. The company’s solutions claim a 90% reduction in energy use and carbon emissions compared to traditional GPU setups, which the company equates to planting thousands of trees. This makes it a compelling choice for large-scale deployments in Smart Cities or Video Management Systems where scaling up hardware usually leads to prohibitive electricity costs and significant heat management issues.
Pros & Cons
Saves approximately 94% in electricity costs over five years compared to standard GPGPUs.
Maintains high AI precision by using IQ8 technology for INT8 quantization with FP32 accuracy.
Operates at ultra-low power levels, with the DX-M1 unit consuming only 5W during operation.
Recognized with multiple industry honors including the CES 2024 Triple Honoree distinction.
Reduces AI-related carbon emissions and energy use by 90% for sustainable operations.
Requires physical hardware acquisition and integration rather than being a cloud-only service.
Specific per-unit pricing for hardware is not publicly listed on the primary landing page.
Optimization for the specialized NPU architecture may involve a learning curve for the SDK.
Use Cases
Industrial engineers can integrate DX-M1 modules into smart factory equipment to automate quality inspections without high energy overhead.
Smart city planners can deploy low-power AI gateways for real-time traffic monitoring and video management across urban infrastructure.
Automotive developers can utilize the DX-H1 series to power on-device smart mobility features while minimizing heat generation in vehicle systems.
Platform
Task
Features
• industrial-grade hardware designs
• multi-model inference support
• on-device llm optimization
• int8 with fp32 precision
• ultra-low 5w power consumption
• dxnn sdk
• iq8 intelligent quantization
• dx-m1 ai accelerator
FAQs
How energy-efficient is the DX-M1 NPU compared to GPUs?
The DX-M1 consumes only 5W of power while outperforming a 40W GPGPU by 240% in efficiency. This high efficiency can lead to a 94% reduction in electricity costs over a five-year period.
What is DEEPX IQ8 technology?
IQ8 is an intelligent quantization technology that allows INT8 operations to achieve the accuracy level of FP32. This allows for high-precision AI inference without the power overhead of floating-point operations.
Which industries are DEEPX solutions optimized for?
The products are specifically designed for edge computing, smart mobility, smart factories, smart cities, and advanced video management systems that require on-device processing.
What software tools are provided for developers?
DEEPX provides the DXNN SDK, which allows developers to port and optimize their AI models for DEEPX hardware. It is designed to facilitate effortless integration into various edge devices.
Does DEEPX offer full AI systems or just chips?
DEEPX offers a comprehensive range of products including individual AI chips, high-performance modules, and complete AI systems like gateways, industrial PCs, and workstations.
Pricing Plans
DX TechBridge Program
Unknown Price• DX TechBridge Kit
• Hardware evaluation access
• SDK documentation
• Technical support
• Developer resources
Commercial Hardware
Unknown Price• DX-M1 NPU Chips
• AI Modules (M.2)
• AI Systems & Gateways
• DXNN SDK inclusion
• Bulk quantity options
Job Opportunities
Alternative Military Service Program
Optimize edge AI performance with ultra-low power consumption and GPU-level accuracy using award-winning NPU chips and modules for smart industrial applications.
Benefits:
Stock options equivalent to annual salary for all full-time employees
Latest high-spec laptops and standing desks
Support for breakfast, lunch, and dinner
Unlimited snacks, ice cream, and drinks in the office cafe
Fitness center and sauna membership support
Experience Requirements:
Experience not required
Other Requirements:
Candidates with less than 3 years of experience are required to submit their academic transcripts
If any false information is found in application documents, the job offer may be withdrawn
Responsibilities:
Develop ROM boot code and bootloaders
Design and implement a real-time inference engine
Analyze state-of-the-art (SOTA) generative AI models
Develop deep learning compilers optimized for products
Design RTL-based hardware IPs related to AI processor architecture
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Culture Planner
Optimize edge AI performance with ultra-low power consumption and GPU-level accuracy using award-winning NPU chips and modules for smart industrial applications.
Benefits:
Stock options equivalent to annual salary for all full-time employees
Latest high-spec laptops and standing desks
Support for breakfast, lunch, and dinner
Unlimited snacks, ice cream, and drinks in the office cafe
Fitness center and sauna membership support
Experience Requirements:
10 years+ in HR/People Ops
Ideally within a high-growth tech startup or a fast-paced semiconductor/AI environment
Proven experience in environments that demand exceptional levels of dedication
Other Requirements:
Fluent in Korean and English
Bilingual communication skills
Responsibilities:
Lead the design and implementation of DEEPX’s unique organizational culture
Translate the company’s core philosophy into high-impact cultural rituals
Foster a culture where results are the primary measure of success
Ensure all internal communications reflect a high-performance mindset
Design initiatives that safeguard the team’s grit through results
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Android Framework Development Engineer
Optimize edge AI performance with ultra-low power consumption and GPU-level accuracy using award-winning NPU chips and modules for smart industrial applications.
Benefits:
Stock options equivalent to annual salary for all full-time employees
Latest high-spec laptops and standing desks
Support for breakfast, lunch, and dinner
Unlimited snacks, ice cream, and drinks in the office cafe
Fitness center and sauna membership support
Experience Requirements:
Minimum 3 years of experience
Deep understanding of Android Internals (AOSP)
Experience in Linux-based system programming
Other Requirements:
Strong C++ proficiency
Must be able to pass a rigorous coding test using C++
Responsibilities:
Integrate DEEPX NPU Runtime (RT) libraries into the Android Framework
Develop and modify the lower layers of the Android stack (HAL, Native Daemons)
Implement and optimize the data path between Android Application layer and NPU
Ensure communication between Android NNAPI and DEEPX driver
Trace and resolve complex system-level issues across Hardware, Kernel, and Android layers
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