audio model comparison
Sonic 3.6 vs TTS-1
Sonic 3.6 and TTS-1 are both current audio models, from Cartesia and OpenAI. TTS-1 is 77% cheaper per character than Sonic 3.6, $0.000015 vs $0.000065. On Artificial Analysis Speech Arena, Sonic 3.6 scores 1286 Elo and TTS-1 1090 Elo (Artificial Analysis, measured October 13, 2026).
Data verified October 13, 2026 · Dataset 2026-10-13
Side by side
Standard-tier prices in effect today. The better value in each row is highlighted.
| Fact | Sonic 3.6 | TTS-1 |
|---|---|---|
| Price per character | $0.000065 | $0.000015 (better) |
| Artificial Analysis Speech Arena | 1286 Elo (#3 of 11) (better) | 1090 Elo (#9 of 11) |
| Provider | Cartesia | OpenAI |
| Release date | August 27, 2026 | Not reported |
| Access | API only | API only |
| Context window | Not reported | Not reported |
| Max output | Not reported | Not reported |
| Input | text | text |
| Output | audio | audio |
When to choose each
Sonic 3.6
Best for
- Multilingual speech for voice agents
- Indian-language and Hinglish speech
Watch out for
- Credit-based plans only (1 credit per character); the recorded rate is the Pro plan overage of $65 per 1M characters, falling to $38 on the Scale plan
- Cartesia does not state latency figures for this version
TTS-1
Best for
- Low-latency text-to-speech
Watch out for
- OpenAI no longer lists TTS-1 on its models overview, though its model page and $15 per 1M characters price remain
Sonic 3.6 vs TTS-1 FAQ
Which is cheaper, Sonic 3.6 or TTS-1?
TTS-1 is 77% cheaper per character than Sonic 3.6, $0.000015 vs $0.000065.
Which scores higher on independent benchmarks, Sonic 3.6 or TTS-1?
Sonic 3.6 leads on Artificial Analysis Speech Arena, 1286 Elo to 1090 Elo. Scores are independent evaluations, not either vendor's launch figures.
Related comparisons
Production evaluation
Choosing between Sonic 3.6 and TTS-1?
Public benchmarks narrow the shortlist. We run both on your own tasks, data and cost limits, then build the routing and review controls to run the winner in production.
- A head-to-head evaluation on your real workload
- Routing between models by cost and difficulty