การ์ดจอ Nvidia H800 GPU สำหรับการเรียนรู้ DeepSeek

Engineered for demanding AI development and compute-intensive workflows, the NVIDIA H800 DeepSeek Learning GPU delivers exceptional performance in a versatile form factor. Ideal for researchers, data scientists, and developers, this GPU accelerates deep learning training, inference, and scientific computing across workstations, desktops, and high-performance laptops.

ข้อมูลจำเพาะที่สำคัญ:

• Chipset: NVIDIA H800 (Custom DeepSeek Edition)
• Core Clock: 1,410 MHz (Boost) / 1,065 MHz (Base)
• Video Memory: GDDR6 with 768 GB/s Bandwidth
• Process Technology: 8nm Efficiency
• Power Design: 230W TDP
• API Support: DirectX 12, CUDA, OpenCL
• Interface: PCI Express
• Output: HDMI
• Cooling: Active Fan Solution
• Form Factor: MXM (Modular Design for Laptops/Embedded Systems)
• Dimensions: 268 × 111.15 × 27 mm

Performance Highlights:

• ✅ High-Speed Memory: 768 GB/s GDDR6 bandwidth for rapid data processing.
• ✅ Optimized AI Workloads: Accelerates TensorFlow, PyTorch & CUDA-based applications.
• ✅ Flexible Deployment: MXM form factor enables integration into workstations, desktops, and compatible laptops.
• ✅ Energy-Efficient: 8nm process technology balances power and performance.

การใช้งาน:

• Deep Learning Training & Inference
• Scientific Simulation & HPC
• AI Development Workstations
• Edge Computing & Mobile Labs
• Advanced Rendering & Visualization

Product Details:

• Model Number: 900-21001-0020-100
• Condition: New (Sealed/Unused)
• Origin: Designed and manufactured in China

Why Choose the H800 DeepSeek GPU?

This specialized GPU bridges the gap between data-center-scale AI and edge deployment, offering researchers and engineers a powerful, flexible solution for next-gen AI projects. With its unique MXM form factor, it brings data-center-grade acceleration to compact systems—perfect for prototyping, on-site testing, and mobile workstations.

เหมาะสำหรับ:

• AI startups scaling training workloads
• Universities running GPU-accelerated labs
• Edge AI deployment in robotics/IoT
• Developers needing portable compute power