AssemblyAI uses EC2 Spot to optimize speech transcription inference costs
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On November 14, 2026, the official AWS Machine Learning Blog (first-hand source) published a post describing AssemblyAI's practices for optimizing speech-to-text inference costs. The article states that AssemblyAI built a mixed-instance architecture on Amazon ECS, combining EC2 Spot instances with On-Demand GPU instances to run speech-to-text inference workloads. With this Spot and On-Demand hybrid deployment, AssemblyAI achieved 70% savings in inference compute costs compared with using all On-Demand instances. The case is currently disclosed by AWS in an official blog post, with no further developments reported.
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- AWS Machine Learning BlogCost-optimizing AssemblyAI speech-to-text inference on AWS with Amazon EC2 Spot
The AWS official blog describes AssemblyAI's architecture for running speech-to-text inference on Amazon ECS using a mix of EC2 Spot and On-Demand GPU instances, achieving 70% savings in inference compute costs compared with On-Demand.
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