Deepgram vs. AssemblyAI (2025): Which STT API Should You Choose?

If you ask any developer "What is the best Speech-to-Text API?", you will get one of two answers: Deepgram or AssemblyAI.

These two companies have effectively cornered the market for enterprise-grade transcription. They are the Coca-Cola and Pepsi of Voice AI.

But they are philosophically very different.

Deepgram is obsessed with Speed and Throughput.
AssemblyAI is obsessed with Understanding and Accuracy.

In this detailed comparison, we pit their flagship models—Deepgram Nova-3 and AssemblyAI Universal-2—against each other to help you pick the winner for your stack.

1. Speed & Latency (The "Real-Time" Test)

If you are building a voice bot (like a Siri for customer support), latency is your god. You need the bot to reply before the user gets bored.

Deepgram Nova-3:
- Architecture: End-to-end Deep Learning (proprietary).
- Latency: Consistently <300ms.
- Vibe: Feels instantaneous. It’s built for streaming.
AssemblyAI Universal-2:
- Architecture: Conformer-based.
- Latency: 300ms - 600ms (Streaming).
- Vibe: Slight delay. Perfectly fine for captions, but noticeable in a rapid-fire conversation.

Winner: 🏆 Deepgram. If speed is your #1 priority, stop reading and use Deepgram.

2. Accuracy (The "Trust" Test)

Speed doesn't matter if the bot hears "cancel my order" as "cancel my border."

Deepgram Nova-3:
- WER: ~5.3% (Claimed), ~18% (Independent benchmarks on noisy audio).
- Strengths: incredibly fast, good enough for 95% of conversations.
- Weaknesses: Sometimes struggles with complex entity formatting (e.g., "ISO 9001" vs "iso nine thousand one").
AssemblyAI Universal-2:
- WER: ~14.5% (Independent benchmarks).
- Strengths: Best-in-class handling of proper nouns, punctuation, and capitalization. It "understands" the context better.
- Weaknesses: Slightly slower processing time to achieve this precision.

Winner: 🏆 AssemblyAI. For medical, legal, or financial use cases where every digit matters, AssemblyAI has the edge.

3. Pricing (The "Bill" Test)

Both are cheaper than Google/AWS, but how do they compare to each other?

Deepgram:
- Rate: ~$0.0043 / minute ($0.26 / hour).
- Billing: Per-second (True PAYG).
- Hidden Value: No rounding up means short utterances cost almost nothing.
AssemblyAI:
- Rate: ~$0.0061 / minute ($0.37 / hour).
- Billing: Per-second.
- Note: Prices were reduced in 2024 to compete with Deepgram.

Winner: 🏆 Deepgram. It is ~30-40% cheaper for pure transcription.

4. Features (The "Intelligence" Test)

This is where AssemblyAI flexes its muscles.

Deepgram:
- Focuses on the "transcription" layer.
- Has "Flux" for turn detection and some NLU features, but they are secondary to the core STT engine.
AssemblyAI:
- Offers a full Audio Intelligence suite.
- PII Redaction: Built-in.
- Sentiment Analysis: Built-in.
- Auto Chapters: Built-in.
- Speaker Diarization: Often cited as more accurate in distinguishing speakers.

Winner: 🏆 AssemblyAI. If you need to analyze the call, not just transcribe it, AssemblyAI saves you from building a separate NLP pipeline.

5. Deployment Options

Deepgram: Cloud, VPC, and On-Premise.
AssemblyAI: Cloud. (On-Premise is available but typically reserved for very large enterprise contracts).

Winner: 🏆 Deepgram (for flexibility).

Final Verdict: Which One?

The "Rule of Thumb"

Building a Voice Bot? Use Deepgram.
Building a Transcription Tool (like Otter.ai)? Use AssemblyAI.