To The Moon

$NVIDIA Corp(NVDA)$ to the moon

nvidia's b200 gpu outperforms intel's gaudi3 by 1.5 times in ai computing performance with 20 petaflops of fp8 performance

nvidia's rapid iteration rate also contributes to its dominance with fp6 performance being 2.5 times that of the previous h100 generation providing unparalleled computing power for the ai and data center markets

although intel has made improvements in energy efficiency, nvidia still holds the lead in crucial ai performance indicators

1. process technology:

   $Meta Platforms, Inc.(META)$ 's mtia chip adopts 5-nanometer process technology

   $Intel(INTC)$ 's gaudi 3 ai accelerator also uses 5nm process

   nvidia's on 3nm

2. performance enhancement:

   meta's new generation mtia chip doubles both computing power and memory bandwidth

   intel claims gaudi 3's bf16 performance is four times that of the previous generation product, with network bandwidth twice that of the previous generation product

   nvidia's h100 gpu achieves 20 petaflops of fp8 performance in ai computing performance, 2.5 times that of the previous h100 computation performance, far ahead

3. memory and bandwidth:

   gaudi 3 is equipped with up to 128gb of hbm2e memory with a peak bandwidth of 3.7tb/s (what's the use hahaha the performance is still far behind)

   

4. efficiency:

   intel played a little trick while gaudi 3 claims to be more than twice as energy efficient as nvidia's h100 gpu, remember that other computing cards will only have such efficiency in small-scale calculations. nvidia's h200 gpu has no rival in large-scale ai training tasks

5. ecosystem and software support:

   nvidia's deep integration of the cuda platform and ai frameworks provides developers with powerful tools and resources, forming an insurmountable moat

   although meta and intel chips have improved performance, they lack recognition from the market as emerging products without frameworks. how can enterprises invest in and use them?