Lower Your Deepgram Bill with an On-Device Alternative
Deepgram bills per minute of audio processed, so your speech-to-text cost scales directly with how much you transcribe. In production, that bill has no ceiling.
Cheetah Streaming Speech-to-Text and Leopard Speech-to-Text convert voice to text on-device: cost-effective at scale, private, and offline.
How Deepgram Pricing Works?
Deepgram uses usage-based, pay-as-you-go pricing. Speech-to-text is billed by the length of audio you process, presented as a per-minute rate that varies by model and by whether you stream in real time or transcribe pre-recorded files. Text-to-speech and the Voice Agent API are billed on their own usage meters. You can prepay credits or move to a committed plan, and higher volume unlocks discounts.
The model is straightforward, but the structure means one thing for product teams with high-volume use cases: unbounded transcription cost.
Why the Bill Grows at Scale?
Usage-based cloud pricing is fine at prototype volume. In production it becomes the problem. Every call transcribed, every meeting captioned, every voice agent turn processed adds minutes to the meter, and the cloud bill climbs with adoption. Success makes it worse: the more audio you handle, the more you pay, with no upper bound. Streaming workloads that run continuously are especially exposed.
On-Device Speech-to-Text: Cost-Effective at Scale
Cheetah Streaming Speech-to-Text handles real-time transcription and Leopard Speech-to-Text handles pre-recorded audio, both entirely on the device or your own server with flexible usage tracking methods at scale.
On-Device Deepgram Alternatives: Deployment and Cost Model
Cloud engines like Deepgram are strong on raw accuracy; the honest on-device case is deployment, privacy, efficiency, and cost at scale, at production-grade accuracy.
| Factor | Picovoice | Deepgram |
|---|---|---|
| Deployment | On-device / on-prem | Mainly cloud API, with self-hosting option |
| Audio handling | Stays on device, offline | Sent to the cloud or another server |
| Latency source | No network round trip | Network dependent |
| Footprint | 34 MB | Cloud infrastructure |
| Cost model | Cost-effective at scale, no unbounded cloud bill | Per minute of audio, grows with usage |
Check Picovoice's real-time transcription benchmark for more metrics
Try On-device Streaming Speech-to-Text
When Deepgram is the Better Fit?
Deepgram is a strong choice when you're prototyping, want a fully managed cloud service, or are building applications where volatile latency doesn't matter.
On-device STTs win when you are transcribing large volume, latency matters for real-time applications, or privacy and compliance are important for users.