Home Hardware Tutorial Hardware News AMD\'s Radeon Instinct MI300X crushes RTX 4090 in OpenCL benchmark to claim the top spot, but gamers can relax

AMD\'s Radeon Instinct MI300X crushes RTX 4090 in OpenCL benchmark to claim the top spot, but gamers can relax

Jun 18, 2024 pm 01:36 PM
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AMD\'s Radeon Instinct MI300X crushes RTX 4090 in OpenCL benchmark to claim the top spot, but gamers can relax

Launched around six months ago in December of 2023, AMD's Radeon Instinct M1300X professional graphics cad has made its debut on Geekbench's OpenCL benchmark. As is to be expected from the herculean enterprise-grade GPU, it has swiftly claimed the throne, obliterating everything below it - including the RTX 4090.

Before going any further, let us first take a quick look at the Instinct MI300X's specs: packs 19,456 shader units, 192 GB of HMB3 memory with 10.3 TB/s of bandwidth, 1216 matrix cores, and a TDP of a whopping 750 watts. It is not surprising at all that the MI300X scored a massive 379,660 on the OpenCL benchmark, when its specs are kept in mind, comfortably ahead of the RTX 4090 which scored ~320,000. This behemoth of a chip is primarily a competitor to Nvidia's data center offerings such as the H100 'Hopper' GPU.

AMD\'s Radeon Instinct MI300X crushes RTX 4090 in OpenCL benchmark to claim the top spot, but gamers can relax

Pitting theMI300Xagainst theRTX 4090is hardly a fair comparison - the RTX 4090 is a$1,700 consumer gaming GPUwhile the MI300X is a data center GPU that is priced north of $15,000. The MI300X is tailor-designed for data centers, AI, and high-performance computing tasks that require vast amounts of memory and obscene amounts of processing power, while the RTX 4090 caters to gamers and creatives with far more humble needs.

Not that it needs to be said, but data center GPUs like theMI300Xwill not be replacing gaming graphics cards anytime soon. When it comes to the requirements of data center GPUs, they are quite different from those of gamers. Primarily, an increased priority is asserted towards computational efficiency, on-the-fly memory correction, and large-scale data handling - as in the case of AI workloads. Gaming GPUs on the other hand, are optimized for real-time rendering, significantly lower power consumption, and cost-effectiveness. Considering the above points, for the majority of us, the MI300X defeating theRTX 4090is hardly of any particular relevance.

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