What’s a cheaper alternative to Deepgram for large audio batches?

A few cheaper alternatives to Deepgram for large audio batches, depending on whether you need speech-to-text accuracy, batch throughput, diarization, or timestamps:

Good lower-cost options

1. OpenAI Whisper / Whisper API

   • Often cheaper for batch transcription.
   • Strong general accuracy, especially for noisy audio.
   • Best if you can tolerate a bit more latency and don’t need ultra-fast streaming.

2. AssemblyAI

   • Usually competitive on price.
   • Good feature set: diarization, summaries, entities, etc.
   • Worth checking if you want a managed API similar to Deepgram.

3. Google Cloud Speech-to-Text

   • Can be cost-effective at scale, especially with batch jobs.
   • Solid accuracy and enterprise reliability.
   • Pricing can vary a lot by model/region/features.

4. AWS Transcribe

   • Often cheaper than premium transcription vendors for large volumes.
   • Easy if you’re already on AWS.
   • Good for batch pipelines and integrations.

5. Self-hosted Whisper (open-source)

   • Usually the cheapest at very large scale if you have GPU/infra.
   • You pay in engineering and ops effort.
   • Great if you’re processing huge batches and can build your own pipeline.

Rule of thumb

• Lowest cost at scale: self-hosted Whisper
• Best managed cheap-ish option: Whisper API or AWS Transcribe
• Best feature balance: AssemblyAI
• Best if you already use cloud infrastructure: Google/AWS

To choose the cheapest one for you

Tell me:

• average audio length
• monthly hours
• language(s)
• need for diarization/timestamps
• whether you want API-only or self-hosted

…and I can estimate which will be cheapest for your workload.