Deepgram vs AssemblyAI
Head-to-head STT comparison for voice AI builders
Every number cited. Every source linked. No affiliation with either provider.
Quick Verdict
AssemblyAI wins on price ($0.0025/min) and English WER (5.9%). Deepgram wins on streaming latency (150–300ms), language support (36 languages), and domain-specific accuracy for medical and financial audio. Both use per-second billing, which saves 30–40% over block billing for typical voice agent interactions.
Side-by-Side Comparison
Based on publicly available data as of March 2026. Actual performance may vary.
Deep Dive: Accuracy
Word Error Rate (WER) is the standard accuracy metric for speech-to-text, measuring the percentage of incorrectly transcribed words. Lower is better. However, WER comparisons across providers are inherently approximate because each provider uses different test conditions, audio datasets, and evaluation methodologies.
AssemblyAI reports a 5.9% WER for their Universal-3 Pro model, measured across 26 English evaluation datasets. This is the lowest published WER in the STT market for English transcription as of March 2026. Their benchmark covers a broad mix of audio types including podcasts, earnings calls, phone calls, and meetings.
Deepgram reports a 6.84% WER for Nova-3 in streaming mode. This figure comes from Deepgram's own testing on their evaluation set. Deepgram's model is specifically trained on medical, financial, and call center audio, which may produce lower error rates on those domain-specific inputs compared to general-purpose benchmarks.
An independent benchmark by AssemblyAI places Deepgram at 8.1% WER on their evaluation set. The discrepancy between Deepgram's self-reported 6.84% and AssemblyAI's measured 8.1% illustrates the methodological differences between provider-reported benchmarks. Different test sets, audio conditions, and pre-processing steps all affect the final number.
Accuracy note: Provider-reported WER benchmarks use different test conditions, making direct comparison approximate. WER varies significantly by audio type, background noise level, speaker accent, and domain vocabulary. We recommend running your own evaluation on audio samples representative of your production workload.
Deep Dive: Cost Analysis
AssemblyAI's $0.0025/min base rate makes it the cheapest English STT provider by a significant margin, roughly one-third the cost of Deepgram's pay-as-you-go rate. However, the base rate tells only part of the story. AssemblyAI charges separately for add-on features: speaker diarization adds $0.0003/min and PII redaction adds $0.0013/min. With both add-ons enabled, the effective rate rises to $0.0041/min, still cheaper than Deepgram, but the gap narrows.
AssemblyAI base rate
Universal-3 Pro
Deepgram pay-as-you-go
Nova-3
Deepgram offers a Growth plan at $0.0065/min, but it requires a $4,000/year minimum commitment. This plan only makes economic sense if your monthly volume exceeds approximately 51,000 minutes ($4,000 / 12 months / $0.0065 per minute). Below that threshold, the pay-as-you-go rate of $0.0077/min is more cost-effective.
Monthly Cost at Scale
| Monthly Volume | Deepgram (PAYG) | Deepgram (Growth) | AssemblyAI |
|---|---|---|---|
| 10,000 min | $77 | $65* | $25 |
| 50,000 min | $385 | $325 | $125 |
| 100,000 min | $770 | $650 | $250 |
*Deepgram Growth plan requires $4,000/yr minimum commitment. All figures use base rates without add-ons.
At 100,000 minutes per month, AssemblyAI saves $520/month over Deepgram's Growth plan ($250 vs $650) and $6,240/year. For teams where English-only transcription is sufficient, the cost advantage is substantial. However, this comparison uses base rates only. Teams requiring speaker diarization and PII redaction on AssemblyAI would pay $410/month at that volume, reducing the annual savings to $2,880.
When to Choose Which
Choose AssemblyAI if:
- English-only workloads. Universal-3 Pro supports English exclusively but delivers the lowest WER (5.9%) and the lowest cost ($0.0025/min) in this comparison.
- Price-sensitive applications. At roughly one-third the cost of Deepgram, AssemblyAI reduces STT spend meaningfully for high-volume deployments.
- Modular add-on features. Speaker diarization, PII redaction, and sentiment analysis are available as separate line items, so you pay only for what you use.
Choose Deepgram if:
- Multilingual requirements. Nova-3 supports 36 languages, making it the clear choice for applications serving a global user base.
- Streaming latency is critical. Deepgram's 150–300ms streaming latency is the fastest published figure in the STT market. For real-time voice agents where every millisecond matters, this advantage is meaningful.
- Domain-specific audio. Nova-3 is trained on medical, financial, and call center audio. If your transcription workload involves specialized vocabulary (drug names, financial terms, industry jargon), Deepgram's domain training likely produces lower error rates than general-purpose benchmarks suggest.
For teams building real-time conversational voice agents that serve English-speaking users, AssemblyAI's combination of price and accuracy is hard to beat. For teams building multilingual applications, low-latency streaming pipelines, or domain-specific transcription for healthcare and finance, Deepgram remains the stronger choice despite the higher per-minute cost.
Both providers use per-second billing, which aligns cost with actual usage. This is a meaningful advantage over Google Cloud's 15-second block billing or Azure's per-minute billing for voice agent workloads where typical utterances are 3–8 seconds. Neither provider locks you into a billing model that inflates costs for short speech segments.
Sources
- [1]Deepgram Pricing
Last verified: Mar 19, 2026
- [2]AssemblyAI Pricing
Last verified: Mar 19, 2026
- [3]Deepgram STT Accuracy & Latency Comparison
Last verified: Mar 4, 2026
- [4]AssemblyAI Voice AI Stack
Last verified: Mar 4, 2026
Disclaimer: STT WER, latency, noise robustness, and multi-language data are independently tested by Speko using automated benchmarks. Pricing reflects publicly available rates. TTS, LLM, S2S, and platform data sourced from official documentation. We are not affiliated with any provider listed.
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