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The original was posted on /r/machinelearning by /u/pmv143 on 2025-09-10 19:39:51+00:00.

NVIDIA dropped MLPerf results for Blackwell Ultra yesterday. 5× throughput on DeepSeek-R1, record runs on Llama 3.1 and Whisper, plus some clever tricks like FP8 KV-cache and disaggregated serving. The raw numbers are insane.

But I wonder though . If these benchmark wins actually translate into lower real-world inference costs.

In practice, workloads are bursty. GPUs sit idle, batching only helps if you have steady traffic, and orchestration across models is messy. You can have the fastest chip in the world, but if 70% of the time it’s underutilized, the economics don’t look so great to me. IMO