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Deepgram Aura 2
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Deepgram Aura 2 is a closed-weights text-to-speech model from Deepgram, released April 2025.
Catalogue identity notes
DeepGram Aura-2 as explicitly linked in the result row.
Model information sources
Score within the Vapi Humanness · Bradley–Terry rating, 2026-09-25 snapshot comparison set only.
$ how it compares
The text-to-speech models ranked either side of Deepgram Aura 2, out of 148 with a score.
| # | model | score | where |
|---|---|---|---|
| 60 | 57±2 | local | |
| 61 | 57±7 | api $30.00/M chars | |
| 62 | 57±3 | api $30.00/M chars | |
| 63 | 57±2 | local | |
| 64 | 55±10 | local |
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$ what it's good at
other tests6 not in a task · 96% of its score
| test | result | vs the others in its run | counts |
|---|---|---|---|
| EmergentTTS · 6-category preference | 25.8% ✎ | ▅▅▃▃█▅▅▃·▃·▅ beats 7/16 | 30% |
| Rime ContentBench · paired human preference vs Rime Coda (US English) | 0.15 / 2 ✎ | ▄·▄········█ beats 2/3 | 20% |
| Rime SupportBench · paired human preference vs Rime Coda (US English) | -0.37 / 2 ✎ | █·······█·██ beats 1/3 | 18% |
| RW-Voice-EQ TTS · Reliability (human) | 3.60 / 5 ✎ | █·▄······▄·▄ beats 1/4 | 13% |
| EmergentTTS · v1 paper automatic MOS (WV-MOS) | 4.33 / 5 ✎ | ▄·█·█▄····█▄ beats 8/8 | 7.3% |
| EmergentTTS · 6-category WER | 16.8% ✎ | ▂▄··▂▄▄··█▄▆ beats 7/16 | 6.9% |
$ where to run it
Through an API
api · $30.00/M chars · deepgram.com ↗ · price sourceUSD per 1M input characters: Deepgram lists Aura-2 text-to-speech at $0.030 per 1k characters, pay as you go (x1000); Growth plan $0.027 per 1k. Product: Deepgram TTS API. API model: aura-2. Settings: pay-as-you-go. Price basis: published list rate. Exclusions: Growth-plan prepay discount. Currency: USD. Deepgram official pricing page, observed 2026-09-25.
$ how the score was worked out · Rime Alpha TTS Benchmark v1.0… 38%, EmergentTTS-Eval six-category… 37%, RW-Voice-EQ Bench (Hume AI) 13% and 1 more
Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works
| source | results | share of the score |
|---|---|---|
| 2 | 38% | |
| 2 | 37% | |
| 1 | 13% | |
| 1 | 7% | |
| prior · pull toward the middle | 4% | |
| weighted average | = 56.5 |
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data updated · sources and licences · json