Self-Hosting Whisper for Speech-to-Text: What Are Your Options?

OpenAI’s Whisper is a speech-to-text model that can be used in many different ways: to transcribe meetings and interviews, generate subtitles, process customer calls, or turn medical consultations and clinical notes into text.

If you’re thinking about adding Whisper to your application, one of the first questions is where to run it. You can use OpenAI’s hosted API, or self-host Whisper on infrastructure of your choice.

In this article, we’ll look at the main options for self-hosting, from your own servers and cloud VMs to running Whisper on a managed service like a PaaS.

And because we’ve been getting questions about self-hosting Whisper on Scalingo, we’ll also show you how our DevRel team put it to the test.

Using Whisper through OpenAI's API

The most straightforward way to use Whisper is through OpenAI’s API. Your application simply sends audio to OpenAI for transcription and receives the resulting text, while OpenAI manages the models and infrastructure behind the service.

The main advantage is convenience: you don’t need to deploy or operate Whisper yourself, making it relatively quick to integrate into an application. Using OpenAI’s API also gives you access to newer generations of transcription models as they become available, without having to manage model deployment or updates yourself.

Using the API does, however, mean that your audio is processed on OpenAI’s infrastructure. Depending on your application, you may want more control over where that processing happens, the infrastructure you use, or the Whisper model and implementation you run.

What are your options for self-hosting Whisper?

There are a few options for self-hosting Whipser: You can run Whisper on your own infrastructure, on a cloud VM, or use a managed platform such as a PaaS. The right option depends on the amount of audio you need to process, the performance you expect and, importantly, how much of the underlying infrastructure you want to manage yourself.

Here’s how the three approaches compare:

Self-hosting Whisper on your own infrastructure

The most hands-on option is to run Whisper on your own physical servers, whether on your premises or in a private data center. This gives you a high degree of control over where Whisper runs, how the environment is configured, who can access it, and whether you use CPUs or GPUs.

For organizations that already operate their own infrastructure, particularly those with strict data-location or infrastructure requirements, this can make sense.

If you don’t already manage physical infrastructure, however, it’s a significant undertaking. Running Whisper becomes only one part of the job: you also need to procure and configure the hardware, secure and update the servers, monitor them, handle failures, plan backups and redundancy, and add capacity as your transcription needs grow.

You also have to plan for peak demand yourself. If your workload suddenly requires more processing power, scaling isn’t simply a matter of changing a setting, you may need to provision additional hardware.

In other words, on-premises gives you maximum control, but also maximum responsibility. If owning and operating servers isn't already part of your organization’s expertise, cloud infrastructure is usually a more practical place to start.

Self-hosting Whisper on a cloud VM

If you want to run Whisper yourself without owning and maintaining physical servers, another option is to use a virtual machine (VM) from a cloud provider. Providers such as AWS, Google Cloud, Azure, OVHcloud or Scaleway let you rent computing resources and choose the CPU, memory and, when needed, GPU resources for your workload.

Compared with running your own physical infrastructure, the cloud provider takes care of the underlying hardware. You can provision additional resources without buying new servers yourself, and change your setup as your needs evolve.

However, you’re still managing a server. Your team is responsible for configuring the operating system and Whisper environment, installing and updating dependencies, securing the VM, monitoring it and deciding how your application should scale.

For teams with the technical resources to manage cloud infrastructure, this offers considerable flexibility. But if your goal is to self-host Whisper without becoming responsible for the servers it runs on, there’s another option: a Platform as a Service.

Self-hosting Whisper on a Platform as a Service (PaaS)

The third, and easiest option to self-host Whisper, is on a Platform as a Service (PaaS). Like a cloud VM, the application runs on infrastructure provided by someone else, but there’s an important difference: you don’t have to manage the server yourself.

Instead of configuring a VM, maintaining its operating system and handling server updates, you deploy your application and specify the resources it needs. The platform takes care of the rest.

For a Whisper application, this means you can choose the model and implementation you want to run, allocate the necessary CPU and memory, and scale (or set up autoscaling) for those resources as your needs change, without having to administer the machines they run on.

There are also trade-offs when choosing a PaaS though. A PaaS gives you less control over the underlying hardware than managing your own server, and the resources available depend on the platform. If your workload requires specific GPUs or highly specialized infrastructure, for example, a VM or dedicated infrastructure may be more appropriate.

But for many workloads, a PaaS provides an interesting middle ground: you self-host Whisper and retain control over your application, without taking on server administration.

Why run Whisper on Scalingo’s PaaS ?

So, where does Scalingo fit into all of this?

Scalingo is a platform-as-a-service provider that combines the simplicity of a PaaS with European hosting and options for applications with specific security or regulatory requirements. Our infrastructure is hosted in France, which is particularly relevant when the audio processed by Whisper contains sensitive data.

Take healthcare, for example. A recording of a medical consultation can contain personal health data before Whisper has even produced a transcript. Where that audio is processed therefore matters just as much as where the resulting transcript is stored. Scalingo is HDS certified for health data hosting, making it suitable for applications that need to process this type of data.

For other applications with particularly high security or sovereignty needs, Scalingo also offers a region built on OUTSCALE’s SecNumCloud-qualified infrastructure.

Of course, not every Whisper application will need these options. But when data location or regulatory requirements matter, they should be part of the hosting choice from the start.

Demo: deploying Whisper on Scalingo

Our DevRel team recently put together a working example to show how easy it is to deploy Whisper on Scalingo.

For the demo, we built a small speech-to-text application using faster-whisper and deployed it on our platform. The application lets you send audio for transcription, with the Whisper model size configurable depending on your needs.

The deployment itself follows the same workflow as any other Python application on Scalingo: once you push the application, Scalingo detects the Python environment, installs its dependencies and starts it.

If you want to reproduce the setup, our DevRel team documented the process from start to finish, including choosing and sizing the Whisper model, deploying the application and testing the transcription endpoint.

Follow the step-by-step tutorial/demo to deploy Whisper on Scalingo

FAQ

Is self-hosting Whisper better than using OpenAI’s API?

Not necessarily. They solve different needs. An API reduces the infrastructure you need to operate, while self-hosting gives you greater control over the model, infrastructure and where audio processing takes place. The right choice depends on your application and requirements.

What is the difference between Whisper and faster-whisper?

Whisper is the speech recognition model released by OpenAI. faster-whisper is an alternative implementation designed to run Whisper models more efficiently. It uses the same Whisper models, but a different inference engine.

Can you self-host Whisper without managing your own servers?

Yes. Using a hosting solution such as a PaaS allows you to deploy and run a Whisper application without administering the underlying servers yourself. You still need to choose and configure your Whisper application and allocate appropriate resources, while the platform handles much of the infrastructure underneath.

Can Whisper be used for healthcare applications?

Yes. Whisper can provide the transcription component of applications such as medical consultation transcription or clinical voice notes. Because the audio itself may contain health data, healthcare applications also need to consider where that audio is processed and stored and which regulatory requirements apply to their infrastructure. In France an HDS-certified hosting provider like Scalingo will generally be required.

Where should I host Whisper if my application handles health data?

If your application processes health data in France, you may need to run Whisper on HDS-certified infrastructure.

Scalingo is HDS certified for health data hosting, and lets you self-host your Whisper application on our PaaS while meeting this hosting requirement.