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audio model comparison

Eleven Flash v2.5 vs Sonic 3.6

Eleven Flash v2.5 and Sonic 3.6 are both current audio models, from ElevenLabs and Cartesia. Eleven Flash v2.5 is 38% cheaper per character than Sonic 3.6, $0.00004 vs $0.000065. On Artificial Analysis Speech Arena, Eleven Flash v2.5 scores 1078 Elo and Sonic 3.6 1286 Elo (Artificial Analysis, measured October 13, 2026).

Data verified October 13, 2026 · Dataset 2026-10-13

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Side by side

Standard-tier prices in effect today. The better value in each row is highlighted.

FactEleven Flash v2.5Sonic 3.6
Price per character$0.00004 (better)$0.000065
Artificial Analysis Speech Arena1078 Elo (#11 of 11)1286 Elo (#3 of 11) (better)
ProviderElevenLabsCartesia
Release dateNot reportedAugust 27, 2026
AccessAPI onlyAPI only
Context windowNot reportedNot reported
Max outputNot reportedNot reported
Inputtexttext
Outputaudioaudio

Scores:Artificial Analysis · 2026-10-13

Open both in the interactive comparison

When to choose each

Eleven Flash v2.5

Best for

  • Low-latency multilingual speech

Watch out for

  • Built for latency rather than expressiveness; Eleven v4 Turbo now sells at the same $0.04 per 1,000 characters
Full Eleven Flash v2.5 profile

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
Full Sonic 3.6 profile

Eleven Flash v2.5 vs Sonic 3.6 FAQ

Which is cheaper, Eleven Flash v2.5 or Sonic 3.6?

Eleven Flash v2.5 is 38% cheaper per character than Sonic 3.6, $0.00004 vs $0.000065.

Which scores higher on independent benchmarks, Eleven Flash v2.5 or Sonic 3.6?

Sonic 3.6 leads on Artificial Analysis Speech Arena, 1286 Elo to 1078 Elo. Scores are independent evaluations, not either vendor's launch figures.

Production evaluation

Choosing between Eleven Flash v2.5 and Sonic 3.6?

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