FIELD GUIDE / GOOGLE

Gemini 3.1 Flash TTS Pricing: Audio Output Is Not Text Output

Speech generation must account for both words entering the model and audio tokens leaving it.

Speech generation must account for both words entering the model and audio tokens leaving it.

Commercial evidence policy: The figures in this article are documented first-party list references checked on 25 October 2026, with any original publication or effective date separated in the data files. Account eligibility, geography, tax, billing cadence and volume commitments can alter actual invoices; unknown effective dates remain null.

Model and price unit

Google’s published Gemini 3.1 Flash TTS Preview model identifier is gemini-3.1-flash-tts-preview. The Standard API table lists $1 per million text input tokens and $20 per million output audio tokens. It also lists Batch at $0.50 input and $10 audio output per million tokens. These are developer API token rates, not a subscription seat price or an audio-minute tariff, and the Preview designation is important for rollout or endpoint changes.

Convert seconds only when the official conversion applies

The Google pricing note states that audio tokens correspond to 25 per second. If an audio render produces 100 seconds at that accounting rate, the output is 2,500 tokens, and the $20-per-million audio rate gives $0.05 in output usage. Text input is additional. This is an illustration of the published model-specific conversion: do not copy 25 tokens/second into another vendor’s service or assume it fully predicts every task’s final billed response.

Production quality can change the economics

A narration pipeline usually contains segmentation, pronunciation revisions, take selection, loudness normalisation and quality checks. The list tariff tells you the charged token unit, not how many retries editorial staff will need. For an audiobook or a multilingual campaign, model the accepted audio duration by language and multiply by an explicit attempted-to-accepted output ratio taken from your own data. Include transcription and human review if those are part of the workflow.

What the free labels actually say

The official table shows a free tier option for preview TTS input and output but lists Batch as unavailable on the free tier. Free access can depend on eligibility, quotas, model visibility and policy. Do not extrapolate from a trial account that unlimited free bulk synthesis is available globally. Keep the endpoint ID, language and paid/free tier in each price and QA record. This remains different from ElevenLabs character- or credit-based bundles.

Before choosing a paid tier

Obtain the billing quote for the exact Google product, account geography, tier, model or subscription, currency and commitment length. If the provider offers several kinds of meters, forecast each independently rather than summing quantities in incompatible units. The relevant captured meters here include input_text_tokens_per_1m, output_audio_tokens_per_1m. Build a low, expected and high workload from your own request logs or editorial schedule; a pricing page is not a credible estimate of how many retries or approvals your team will need.

For governance, add an approval threshold for paid overages, reconcile invoices with metered activity, and schedule a quarterly or release-triggered source audit. The absence of an identified enterprise rate, promotional expiry or regional tax line is not evidence that the amount is zero. This guide does not represent a product trial, capability benchmark, procurement offer or warranty of uninterrupted access.

Historical availability and boundaries

Preserve the precise source version, checked date and any stated effective date before reusing these figures. A model launch announcement may confirm an introductory token rate without proving which private offers remain available; a mutable plan page can describe a later product state. If a source changes after this cutoff, publish a new snapshot instead of silently editing the historical record. Specialised product evaluations belong to the relevant AI 02–09 editorial teams, while this article documents the billing model and its limitations.

Sources & Further Reading

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