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15 years of FP64 segmentation, and why the Blackwell Ultra breaks the pattern
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Overview
The RTX 5090 delivers 104.8 TFLOPS of FP32 compute and only 1.64 TFLOPS of FP64 compute, resulting in a 64:1 FP64 to FP32 ratio. Over the past fifteen years, this ratio has widened on consumer GPUs, reflecting a growing divide between consumer and enterprise silicon, which is now being challenged by advancements in AI.
Summary from nicolasdickenmann.com.
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Hacker News · nicolasdickenmann.com
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Based on 5 sampled comments from this thread. Analyzed 2026-02-19.
- Praise: NVIDIA's evolution from graphics chips to GPGPU illustrates their adaptability, showcasing how innovations in one area can lead to breakthroughs in another, like CUDA.
- Praise: The historical context of FP64 capabilities highlights the importance of HPC workloads, which underscores the significance of NVIDIA's strategic decisions in the AI landscape.
- Concern: The article overlooks the cost implications of FP64 units, which could significantly increase GPU prices, raising concerns about market viability for gamers.
- Concern: Regulatory constraints on FP64 performance for consumer GPUs limit their applicability, indicating a significant barrier for developers in high-performance computing sectors.
- Concern: The potential overflow and underflow issues with double-precision implementations could severely impact scientific computing, raising doubts about the proposed solutions.