Side-by-Side Comparison - NVIDIA RTX 4090 & H100 GPUs

To provide a side-by-side comparison of the NVIDIA RTX 4090 and the H100 GPUs, I'll break down the comparison into several key categories. It's important to note that these GPUs serve different purposes, with the RTX 4090 being a high-end consumer graphics card primarily for gaming and creative applications, and the H100 being an enterprise-level data center GPU, optimized for AI and machine learning tasks. Here's a comparison table:


  • Purpose: RTX 4090 is aimed at gamers and creators, while H100 is for AI and high-performance computing.

  • Architecture: Different architectures optimized for their respective uses.

  • Memory: H100 has significantly more and faster memory, catering to its data-intensive tasks.

  • CUDA Cores: H100 has a much higher core count, reflecting its focus on parallel processing for AI and scientific computations.

  • Tensor Cores: More advanced in H100, crucial for AI and machine learning.

  • Ray Tracing Cores: RTX 4090 has dedicated cores for ray tracing, a key feature for realistic gaming graphics.

  • TDP: H100 has a higher power requirement due to its enterprise-level processing capabilities.

  • Performance: Each is optimized for different tasks; RTX 4090 excels in gaming and content creation, while H100 is for AI and computational tasks.

  • Connectivity: RTX 4090 offers standard display outputs, while H100 focuses on high-speed data center connectivity.

  • Market Segment: RTX 4090 is for consumers, whereas H100 targets enterprise and data centers.

  • Price Range: H100 is significantly more expensive, reflecting its enterprise-grade capabilities.

This comparison highlights the fundamental differences between these GPUs, tailored to their specific target applications and market segments.

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