Testing shows the H200 and MI300X falling well behind the RTX 5090, despite both GPUs being significantly more expensive. On average, the RTX 5090 was 20% faster than the MI300X and a whopping 63.7% faster than the H200. At most, the RTX 5090 was 33.7% faster than the Mi300X in MD5 and 93.5% faster than the H200 in SHA-512.
You may like $1,000 bought an RTX 5080 in November 2025, now it only buys an RTX 5070 Ti The GPU benchmarks hierarchy 2026 $5,000 RTX 5090 Lightning Z gets killed in extreme overclocking attempt, thermal shock cracks the GPU core The problem with these AI GPUs is how Hashcat is processed; password cracking relies on 32-bit integer operations and is extremely compute-intensive. It's the exact opposite of machine learning workloads that leverage instruction types such as FP4, BF16, FP8, and INT8.
As a result, Datacenter AI GPUs prioritize these instructions over other instructions. For instance, the H200 has only half as many INT32 cores as FP32 and significantly fewer cores than the RTX 5090, because most of the work it's designed to do is handled by the Tensor cores. Ironically, the MI300X has much greater INT32 performance than the RTX 5090, but still loses due to Nvidia optimizations baked into Hashcat code.
Specops's testing demonstrates how streamlined modern AI GPUs are at their job; there's not much these GPUs can do beyond their intended role. For now, consumer desktop GPUs will remain the fastest for cracking passwords.
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Key considerations
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Reference reading
- https://www.tomshardware.com/pc-components/gpus/SPONSORED_LINK_URL
- https://www.tomshardware.com/pc-components/gpus/tests-show-usd30-000-ai-gpus-are-terrible-password-crackers-h200-and-mi300x-outperformed-by-rtx-5090#main
- https://www.tomshardware.com
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