Many AI Engineers Would Switch From Nvidia To AMD!

TECH NEWS – The justification is performance and cost, so Nvidia’s position could get interesting in the near future.

 

Jeff Tatarchuk, co-founder of TensorWave, wrote on Twitter: “In a recent survey of 82 engineers and AI professionals, 50% of respondents are actively considering the AMD Instinct MI300X GPU. The top three reasons for considering the AMD MI300X are availability, cost, and performance, in that order. We plan to use the MI300X. Are you?” So, according to the independent survey, the better price/performance ratio and greater availability is playing a role in the potential switch.

The MI300X Instinct AI GPU is based on the CDNA 3 architecture (we didn’t misspell it, it’s not RDNA 3!) with up to 153 billion transistors (MI300X) based on 5 and 6 nanometer manufacturing, not to mention double the amount of HBM3 memory (MI250X: 128 GB, MI350X: 256 GB). Compared to Nvidia’s H100, it has 2.4 times the memory capacity, 1.6 times the memory bandwidth, and 1.3 times the FP8 and FP16 TFLOPS processing power. In 1v1 comparisons, it can be up to 20% faster in Llama 2 70B and FlashAttention 2, up to 40% faster in Llama 2 70B in an 8v8 server setup, and up to 60% faster in Bloom 176B.

AMD’s flagship AI accelerator is giving competitors headaches for a reason. The MI300X offers significantly higher performance, and AMD has timed its release perfectly, as Nvidia is now struggling to fill orders and ship chips to customers, significantly slowing their growth with new customers. AMD did not get off to the good start it would have liked, but the survey suggests that their situation could be much better if they take on the competition directly.

So Nvidia should look over its shoulder often, because it’s not only in the desktop market where AMD can show some serious competition (especially due to the fact that there is more VRAM in the Radeon RX 7000 cards compared to the RTX 4000 cards at the same price).

Source: WCCFTech

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