Calculate the true cost of Whisper ASR
Calculate the total cost of ownership of hosting open-source Whisper ASR vs buying a speech-to-text API.
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Should you build in-house or buy? Here are the factors to consider
In-house expertise
Developing an in-house STT solution, especially with real-time streaming, requires advanced AI and data science expertise. Beyond initial deployment, achieving a production-grade system requires fine-tuning, optimization, and ongoing model maintenance.
Customization
While building in-house allows for tailored solutions and unparalleled control, it also adds an additional layer of complexity. In order to fully customize your solution with features like speaker diarization demands extensive time and resources. APIs on the other hand often deliver robust multi-functionality out of the box.
Scalability
Scaling an in-house solution for high-volume transcription requires significant investment in infrastructure. Enterprises must account for additional compute power for parallel processing while most APIs are designed to scale without additional hardware or operational overhead.
Cost
Building a solution in-house can appear cost-efficient in some cases, but when it comes down to it, your total cost of ownership can quickly add up. Expenses related to the costs of hosting, bandwidth, certifications, and security measures are to thank for that. API solutions offer predictable pricing that can help you better forecast and plan ahead of time.
Time and resources
The rapid evolution of AI means that models can become obsolete within just a few years. To stay competitive, it means investing constant time and resources which puts your business at risk of delivering value to your customers.
Decision framework
Depending on your company's current stage of growth, your scalability needs may vary. Below we've segmented the decision framework taking this into consideration along with expected transcription volumes.
Prototyping and validation
~10k hours/month
At this stage, hosting an open-source tool such as Whisper in-house may make sense. At this volume, costs are manageable, however, the trade-off comes at a lack of optimizations, features, and accuracy.
Scaling usage
~20k hours/month
Here's where the investment starts to ramp up. Higher transcription volumes translates to higher costs for full-time employees to optimize the model, maintain the infrastructure, and implement advanced features. At this stage, hosting in-house is rarely worth the effort.
Enterprise level
~150k hours/month
Finally, it's time to really weigh the cost and benefits of hosting in-house when transcriptions start to exceed 150k hours per month. While you most likely have the means to do so, it will often detract from focusing on your core product. Outsourcing to an STT provider however can lead to faster time-to-market and a wiser allocation of resources.
Should you host Whisper? See for yourself
Most teams hosting in-house pick open-source Whisper ASR as their first choice. But how much does it actually cost to host it?
Check out our total cost of ownership calculator to find out.
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