Modal Alternatives for Transcription
Speech to text over a batch of audio, usually Whisper, where the run is long but each file is independent.
What transcription actually needs
Why people look past Modal for this
Per-file independence makes this the easiest job to restart elsewhere; the only real loss is the files already processed if outputs were not written out as they completed. That is exactly the gap Modal does not close: Modal is a serverless platform, not a GPU rental product, and comparing hourly rates is slightly unfair to both of us. If your work is Python functions that should scale to zero between calls and come back in seconds, Modal is better than anything we offer: our jobs scale to zero too, but they restore a box rather than start a container. If it is a long-lived environment you SSH into and keep changing, or a job that runs for hours and has to survive losing its machine, that is our shape.
To be fair, Modal's real strength is real: True serverless: scale to zero, per-second billing, fast container cold starts. You pay only while code runs, which for bursty workloads is dramatically cheaper than any hourly rate.
Live rates for the GPUs transcription wants
Live per-GPU rates from Aquanode's marketplace. Refreshes hourly.
How you run it here today
Run it today with the seeded whisper-transcribe job recipe — a real, publicly-imaged container Aquanode can queue directly, not a template we're promising to build later.
Restoring an environment requires a snapshot that already exists. Stopping a deployment yourself captures it on the way out, so you can bring it back later on any provider. A provider-side termination is different: it is only recoverable if you had already switched automated snapshots on for that deployment, and it costs you the work since the last one. Automated snapshots are opt-in, nothing runs until you start it, and with none running there is nothing to restore.
More alternatives pages
Other workloads on Modal
Transcription alternatives to other clouds
