Amazon iconAmazonAug 27, 2026

Reduce ASR inference costs by 75% with NVIDIA MPS on Amazon EC2

Serving automatic speech recognition (ASR) models at scale is costly when each request uses only a fraction of a GPU. Learn how NVIDIA CUDA Multi-Process Service (MPS) with NVIDIA Triton Inference Server on Amazon EC2 GPU instances cuts GPU infrastructure by 75% while holding sub-second latency at 92.1 requests per second per GPU.

Reduce ASR inference costs by 75% with NVIDIA MPS on Amazon EC2

Share this story

Send the public story page.

Useful takeaways from this story.

Serving automatic speech recognition (ASR) models at scale is costly when each request uses only a fraction of a GPU.

Learn how NVIDIA CUDA Multi-Process Service (MPS) with NVIDIA Triton Inference Server on Amazon EC2 GPU instances cuts GPU infrastructure by 75% while holding sub-second latency at 92.1 requests per second...

Building the complete brief

The page is ready to read now. The fuller skim-friendly version will appear here automatically.

The useful part

Serving automatic speech recognition (ASR) models at scale is costly when each request uses only a fraction of a GPU. Learn how NVIDIA CUDA Multi-Process Service (MPS) with NVIDIA Triton Inference Server on Amazon EC2 GPU instances cuts GPU infrastructure by 75% while holding sub-second latency at 92.1 requests per second per GPU.

Keep reading in the app

Open the app view to save this story, compare related coverage, and continue from the same source.

Open in app