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audio model comparison

Gemini 3.8 Flash-Lite TTS vs GPT-4o Transcribe

Gemini 3.8 Flash-Lite TTS and GPT-4o Transcribe are both current audio models, from Google and OpenAI. GPT-4o Transcribe is 33% cheaper per audio minute than Gemini 3.8 Flash-Lite TTS, $0.006 vs $0.009.

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.

FactGemini 3.8 Flash-Lite TTSGPT-4o Transcribe
Price per audio minute$0.009$0.006 (better)
Artificial Analysis Speech Arena1246 Elo (#5 of 11)Not measured
Artificial Analysis AA-WER v2Not measured3.96 % WER (#6 of 6)
ProviderGoogleOpenAI
Release dateSeptember 22, 2026March 20, 2025
AccessAPI onlyAPI only
Context windowNot reported16,000 tokens
Max outputNot reported2,000 tokens
Inputtexttext, audio
Outputaudiotext

Scores:Artificial Analysis · 2026-10-13Artificial Analysis · 2026-10-13

When to choose each

Gemini 3.8 Flash-Lite TTS

Best for

  • High-volume speech generation such as notifications, IVR prompts and accessibility audio

Watch out for

  • Google doubles the rates on 2027-01-01, to $1.00 input and $12 output per 1M tokens (about $0.018 per minute)
  • No independent speech-quality benchmark is recorded here
Full Gemini 3.8 Flash-Lite TTS profile

GPT-4o Transcribe

Best for

  • Speech transcription

Watch out for

  • OpenAI announced its deprecation on 2026-08-26 and recommends GPT Transcribe, which costs $0.0045 per minute against about $0.006 here
Full GPT-4o Transcribe profile

Gemini 3.8 Flash-Lite TTS vs GPT-4o Transcribe FAQ

Which is cheaper, Gemini 3.8 Flash-Lite TTS or GPT-4o Transcribe?

GPT-4o Transcribe is 33% cheaper per audio minute than Gemini 3.8 Flash-Lite TTS, $0.006 vs $0.009.

Production evaluation

Choosing between Gemini 3.8 Flash-Lite TTS and GPT-4o Transcribe?

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