Deepgram vs Google Cloud Speech-to-Text

On the most heavily weighted attribute, Deepgram charges 0.004 per audio minute for batch versus Google Cloud Speech-to-Text at 0.016, a 4x cost advantage that compounds enormously at call-center scale. For diarizationdiarization - Splitting a transcript by speaker, so you can see who said what., Google includes it at no extra charge, but Deepgram adds only 0.002 per minute, keeping its total even with diarization well below Google's base rate. PII redaction is available from Deepgram as a paid add-on at 0.002 per minute, while Google offers no PII redaction at all, a meaningful gap for compliance-sensitive call centers. Deepgram also supports 50 REST and 150 websocket concurrent connections on its pay-as-you-go plan and includes built-in sentiment analysis, whereas Google has none. The cost lead alone is decisive.

Deepgram leads on three of the five weighted attributes. Its batch price is 0.004 dollars per audio minute versus 0.016 for Google Cloud Speech-to-Text, a 4x cost advantage that matters heavily for metered usage. Deepgram also offers a WebSocket streaming API while Google Cloud Speech-to-Text does not, which is critical for real-time product integrations. Both tools offer similar SDK breadth and word-level timestampsword-level timestamps - The API reports exactly when each word is spoken in the audio, for subtitles and highlighting., and Deepgram supports 100+ audio formats compared to a handful for Google. On price and streaming API alone, Deepgram wins decisively.

The deciding attributes for this use case are dictation platforms, local vs cloud processing, AI formatting and editing features, app pricing, and app integrations. Neither tool publishes verified information on any of these five attributes. Both are cloud-based speech APIs rather than consumer dictation apps, so neither addresses whether audio stays on-device, which operating systems or apps they integrate with as a voice-typing tool, or what a one-time vs subscription purchase looks like for end users. Batch pricing shows Deepgram at 0.004 per minute versus Google at 0.016 per minute, but raw API pricing is not the same as app pricing for a dictation product and carries little weight here. Without facts on the five attributes that decide this use case, no winner can be named.

Both tools offer a HIPAA BAAHIPAA BAA - A signed Business Associate Agreement that lets you handle protected health information under US healthcare privacy law. and SOC 2 Type II certification, so those top-weighted attributes are tied. On PII redaction, Deepgram offers it as a paid add-on at $0.002 per audio minute, while Google Cloud Speech-to-Text has no PII redaction capability at all. This is a decisive gap for clinical transcription, where patient data protection is critical. Both tools support custom vocabulary boosting, so that weight is also tied, and self-hosting is available from both. With PII redaction as the differentiating factor at weight 4 out of 5, and Deepgram being the only option that provides it, Deepgram wins this use case.

For meetings, speaker diarizationdiarization - Splitting a transcript by speaker, so you can see who said what. and summarization carry the most weight. Deepgram offers a native summarization endpoint while Google Cloud Speech-to-Text has none. On diarization, Google includes it at no extra charge while Deepgram charges a paid add-on at 0.002 per audio minute, giving Google an edge on that criterion. However, Deepgram's summarization advantage at weight 4/5 offsets this. Deepgram also handles files up to 2 GB with no hard duration cap, versus Google's 8-hour batch limit, which is generous but more restrictive. Both support word-level timestamps. Google supports 125 languages versus Deepgram's 50, a meaningful gap on the third-heaviest attribute. Weighing all factors, Deepgram's built-in summarization tips the balance despite Google's diarization inclusion and broader language coverage.

Both tools confirm a self-hostself-host - Run the software on your own servers instead of the vendor’s cloud. option is available, which is the top-weighted attribute. Neither tool publishes facts covering open weights license, hardware requirements, maintenance status, or model parameter count, the remaining deciding attributes for this use case. With both tools equal on the only verifiable attribute and no facts to differentiate them across the other four weighted criteria, a genuine tie is the correct finding.

For voice agents, streaming latency and websocket support are the heaviest factors. Deepgram publishes a 300 ms streaming latency and offers a native websocket streaming API, while Google Cloud Speech-to-Text has no websocket streaming API at all, which is a fundamental gap for real-time voice bot use. On streaming price, Deepgram charges 0.005 per audio minute versus 0.016 for Google Cloud Speech-to-Text, a more than 3x cost advantage. On base-plan concurrencyconcurrency - How many phone calls the platform can handle at the same time., Deepgram provides 150 concurrent websocket sessions, while Google Cloud Speech-to-Text cannot offer concurrent streaming sessions since that capability is absent. Both tools support custom vocabulary. The combination of low latency, native websocket support, and lower streaming price makes Deepgram the clear choice.