Hero-Karte für „GPT-Live-1 vs Gemini 3.8 TTS“, mit dem Untertitel „Eine Konversations-Engine und ein Erzähler, nach unterschiedlichen Maßeinheiten abgerechnet“, mit drei Karten mit folgendem Text: „GPT-Live 1: 0,05 $ pro Sprachminute, Vollduplex, 21 Presets plus marin“, „Gemini 3.8 Flash TTS: 9,00 $ pro 1 Mio. Audio-Tokens, etwa 0,0135 $ pro Minute“, „Die Lücke: rund 27x pro Minute, und es ist keine Abrechnung von Gleichem mit Gleichem“, über einer Fußzeile mit dem Text „Preise gemäß den von den Anbietern veröffentlichten Preislisten von OpenAI und Google. Elo gemäß Artificial Analysis Provider Voice Arena, Oktober 2026.“ Das OrcaRouter-Logo ist in der unteren rechten Ecke eingefügt.
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GPT-Live-1 vs. Gemini 3.8 TTS: Der eine führt ein Gespräch, der andere liest ein Skript vor – und nur einer von beiden ist günstig

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Rowan Sterling

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Set G​PT-Live-1 and Gemini 3.8 Flash TTS next to each other on a per-minute meter and the answer looks obvious. G​oogle's narrator bills about 1.35 cents per minute of generated speech at the 2026 rate. O​penAI's conversational model bills 5 cents per minute of open line — and keeps billing while the backend thinks, while the user pauses, and while nothing is being said at all. Roughly a twenty-seven-fold gap, before anyone has asked whether the two are doing the same job.

They are not, and in a way that is more interesting than the usual "different categories" hand-wave. Gemini 3.8 Flash TTS cannot hear. G​PT-Live-1 cannot be batched. And the naming makes this worse than it needs to be, because the phrase G​emini 3.8 TTS — the label half the internet is using — does not correspond to any model you can call.

Zuerst das Namensproblem, denn es entscheidet über den Preis, den Sie nennen.

There is no model called G​emini 3.8 TTS. G​oogle's own documentation uses the phrase as umbrella language for two callable endpoints, and they are priced differently enough that quoting the wrong one is a real error:

• gemini-3.8-flash-tts — die vollständige Tarifstufe, über 130 Sprachen, 0,50 $ pro Million eingegebene Text-Tokens und 9,00 $ pro Million ausgegebene Audio-Tokens, steigend auf 1,00 $ bzw. 18,00 $ am 1. Januar 2027.

• gemini-3.8-flash-lite-tts — 101 Sprachen, gleicher Input-Tarif, 6,00 $ pro Million ausgegebener Audio-Tokens, steigend auf 12,00 $.

• Beide bieten Batch- und Flex-Tarife zum halben Standardpreis ($0,25 Eingabe, $4,50 oder $3,00 Ausgabe) und Priority-Tarife zum 1,8-Fachen ($0,90 Eingabe, $16,20 oder $10,80 Ausgabe).

Audio wird mit 25 Tokens pro Sekunde abgerechnet; daher stammt die Minutenangabe: 25 Tokens × 60 Sekunden = 1.500 Audio-Tokens pro Minute, also entsprechen 9,00 $ pro Million etwa 0,0135 $ pro Minute. Flash-Lite liegt bei etwa 0,009 $.

The status of the model is genuinely unsettled and worth saying out loud, because G​oogle's own surfaces disagree. The G​emini API changelog calls both models generally available. The API model list labels them "New Stable." G​oogle Cloud's text-to-speech documentation describes them as available in Preview through the G​emini Enterprise API only. The announcement blog post, published on 23 September 2026, uses neither word. Anyone writing a procurement note this month should treat the GA label as the changelog's claim rather than a settled fact.

Was jedes Modell tatsächlich tut, wenn man es aufruft

Screenshot of the Google Gemini API documentation for text-to-speech generation, captured 17 October 2026, headed 'Text-to-speech generation (TTS)' and stating that the Gemini API can transform text input into single-speaker or multi-speaker audio, with the Speech and audio documentation navigation showing the Text-to-speech, Voice design, Voice replication and Transcribe pages, and version details for the Gemini 3.8 models.

Gemini 3.8 Flash TTS nimmt Text entgegen und gibt Audio zurück. Es hat keinen Audioeingang, keinen Redezug, den es übernehmen könnte, kein Konzept davon, unterbrochen zu werden, und kein Transkript, das es zurückgeben könnte, denn es hat schlicht nichts gehört. Der unäre Endpunkt liefert WAV mit 24 kHz mono; Streaming liefert headerloses 16-Bit-PCM, wobei mulaw und alaw akzeptiert werden und die Abtastrate konfigurierbar ist. Inline-Regieanweisungen werden als Ereignisse in spitzen Klammern in das Skript geschrieben — <laugh>, <sigh>, <breath>, <short pause> — und der Eingabetext wird ansonsten als wörtliches Transkript behandelt, nicht als Anweisungen. Die Live API unterstützt diese Modelle überhaupt nicht.

G​PT-Live-1 does the opposite job. It is full duplex: it processes incoming audio while producing outgoing audio, decides several times a second whether the user has finished talking, and returns speech-recognition transcripts as part of the session. Its inputs are audio and text; its outputs are audio and text; images and video are unsupported. It streams and supports function calling but not structured outputs, and knowledge cut-off is 31 July 2025. Only one endpoint serves it — v1/live/sessions — and Chat Completions, Responses, Realtime and Batch are all out.

That last detail is the one that ends the comparison for a lot of workloads. If your product renders a script, G​PT-Live-1 is neither the cheap option nor the correct one. If your product answers a phone, Gemini 3.8 Flash TTS is one third of a pipeline that still needs an ASR model and a language model bolted on either side — and the whole point of G​PT-Live-1 is that the seam between those three parts is where conversations break.

A two-column scoreboard titled 'GPT-Live-1 vs Gemini 3.8 Flash TTS — the scoreboard'. Left column GPT-Live-1: 'Job: full-duplex conversation', 'Modalities: audio and text in, audio and text out', 'Price: $0.05 per voice minute, billed per second', 'Voices: 21 presets plus marin, describe-your-own since 16 Oct', 'Languages: presets span 7 languages', 'Independent score: AA speech-to-speech index, GPT-Live-1 configurations listed top-three'. Right column Gemini 3.8 Flash TTS: 'Job: text-to-speech rendering', 'Modalities: text in, audio out only', 'Price: $9.00 per 1M audio tokens, about $0.0135 a minute until 2027', 'Voices: 30 prebuilt plus prompt-designed and cloned', 'Languages: 130-plus on Flash, 101 on Lite', 'Independent score: AA Provider Voice Arena Elo 1,275 at rank 5'. Footer: 'Prices per vendor rate cards; Elo per Artificial Analysis, October 2026.' The OrcaRouter logo is composited in the bottom-right corner.

Die Zahlen – und wem sie gehören

On Artificial Analysis's Provider Voice Arena — a blind-vote Elo board over each vendor's own native voices — G​oogle's new models land mid-field rather than at the top:

Screenshot of the Artificial Analysis Provider Voice Leaderboard, captured 17 October 2026, showing the top of the Elo table with Eleven v4 Turbo first at 1,330 Elo over 1,821 samples, Eleven v4 second at 1,329, Qwen-Audio-3.1-TTS-Plus third at 1,296, Cartesia Sonic 3.6 at 1,285 and Gemini 3.8 Flash TTS at 1,275, with released dates and API pricing columns beside each row.

• Gemini 3.8 Flash TTS — Elo 1.275 auf Rang 5, mit einem 95%-Intervall von ungefähr 1.260 bis 1.290 über 2.783 Stichproben, gelistet mit 16,5 $ pro Million Zeichen.

• Gemini 3.8 Flash-Lite TTS — Elo 1.248 auf Rang 8, Intervall ungefähr 1.234 bis 1.262, 11,0 $ pro Million Zeichen.

• Above both — Eleven v4 Turbo at 1,330, Eleven v4 at 1,329, Q​wen-Audio-3.1-TTS-Plus at 1,296 and Cartesia Sonic 3.6 at 1,285.

G​oogle's own claim is stronger than that board, and it is a vendor claim: the 23 September post says the models took first place on Hume AI's Voice Design Benchmark at 71.4 and led Hume's accent modelling at 60.8, plus top blind-preference positions in Japanese, Brazilian Portuguese, Vietnamese, Modern Standard Arabic, Mexican Spanish and Hindi. Those are G​oogle-reported placements on someone else's evaluation, not a reproduction.

Flipping to the conversational side, G​PT-Live-1's numbers come from a different board entirely. Artificial Analysis's speech-to-speech index — a weighted average of speech reasoning, agentic performance, arena preference and task success — now lists G​PT-Live-1 under named backend configurations rather than as one row: G​PT-Live-1 (Astra, medium) and G​PT-Live-1 (Sol, low) sit at the top of that index, with G​rok Voice 3.0 leading the field. That is a useful reminder that in this architecture the voice model is only half the row; the delegated backend moves the score.

One number that matters and does not exist anywhere: G​oogle publishes no official latency figure for either TTS model. Every time-to-first-audio number in circulation is third-party — one aggregator's p50 sits around 3.47 seconds for Flash TTS and 2.66 for Flash-Lite — and none of it is directly comparable to G​PT-Live-1's conversational cadence, because they measure different things.

Voice-Design ist der Punkt, an dem die beiden zusammenlaufen – und an dem sie wieder auseinandergehen

Beide Anbieter ermöglichen es dir jetzt, eine Stimme mit Worten zu beschreiben. Das ist neu im Jahr 2026, und näher kommen sich die beiden Produkte nicht.

G​oogle's path runs through the G​emini API: a prompt-based voice persona saved persistently as a voice_ ID, voice replication from about a 30-second sample with a consent check, SynthID watermarking and C2PA credentials attached, and a cap of 200 stateful custom voices per project with one-year retention from last use. The written description covers role, accent and vocal traits.

O​penAI's path, released on 16 October 2026 to all API customers, is a POST to /v1/audio/voices with type: "prompt", a name, the description and "model": "auto". Creation is free; using the voice bills at normal session rates. It returns metadata only — no audio, no preview. The qualities you can steer are accent, age, presentation, pitch, timbre, texture, loudness, speech rate and distinctiveness, all expressed as ordinary language with no numeric parameters.

Zwei Unterschiede entscheiden darüber, welche du tatsächlich verwenden kannst:

• Prompt-generated voices on G​PT-Live work only with G​PT-Live. They are explicitly incompatible with the Text to Speech, Realtime and Chat Completions APIs. G​oogle's custom voices are, by contrast, voices for a rendering engine, which is what makes them reusable across a catalogue.

• The organisation cap on O​penAI's side is 100 prompt-generated voices, and it applies to voices generated on behalf of your customers too. G​oogle's ceiling is 200 per project. If you are a platform minting a voice per customer, both numbers are your real product limit, not a footnote.

There is also a difference in what you get back. A G​oogle voice arrives with SynthID and C2PA provenance attached. An O​penAI prompt-generated voice arrives as an ID, a creation timestamp and your own prompt text — and the documentation says outright that generated voices are not guaranteed to be unique. Keep the description under version control; it is the only record of what you asked for.

Wo der Preisunterschied nicht mehr 27× beträgt

The per-minute comparison is the one that gets quoted and it is the one that misleads, because G​PT-Live-1's meter is not measuring the same resource. Three things move the real ratio:

• Idle time is billable. A voice session is billed per second for as long as it is open, including while the backend model is working and while the user is silent. G​oogle's meter only advances when audio is generated. A support call where the user talks for four minutes and your backend thinks for two is six billable minutes on Live and fewer on the renderer — before you have counted the ASR and language-model legs the renderer still needs.

• Die Ausgabelänge ist auf einer Seite kontrollierbar. Ein Rendering-Job ist eine bekannte Größe: Man kann einen 900-Wörter-Artikel kalkulieren, bevor man ihn generiert, und Batch-Tarife halbieren das noch einmal. Bei einer Konversation ist das nicht so.

• The backend is a separate bill. Delegated reasoning and tool use on G​PT-Live-1 are charged at normal model rates on top of the $0.05 a minute, and O​penAI's own cost guidance frames the lever as making the user finish sooner — for example, running a faster backend with parallel tool calls so the conversation ends a minute earlier, saving $0.05. The voice rate is fixed; the session length is the dial.

That last point is where a routing layer stops being a nice-to-have. Client delegation lets you point a G​PT-Live session at your own agent or service, which means the delegated backend can be any model — and the useful version of "any model" is one endpoint and one key rather than a contract per provider. OrcaRouter fronts 200-plus models at provider list price with no markup, so a vendor price cut on the backend side reaches you the day it lands, and automatic failover covers a provider outage without the caller hearing it. If you are building the delegated path, the backend choice is where your cost actually lives; the $0.05 a minute is a constant.

To be precise about the boundary: OrcaRouter does not host G​PT-Live-1 or the G​emini 3.8 TTS models. What it routes is the reasoning side of a delegated Live session.

Zu welchem man greifen sollte

If you are rendering — articles, documentation, video narration, IVR prompts written in advance — Gemini 3.8 Flash TTS is the correct tool and G​PT-Live-1 is roughly 27 times too expensive per audio minute and structurally incapable of the job in batch. Take Flash-Lite if 101 languages cover you, take Batch or Flex rates if latency is not the constraint, and model the January 2027 price doubling from the start, because G​oogle has published it in the same table rather than burying it.

Wenn Sie ein Gespräch führen, ist der TTS-Vergleich ein Kategorienfehler, und die ehrliche Frage lautet anders: Produziert das delegierte Backend eine Antwort schnell genug, dass die Sitzung kurz bleibt? Das ist die Zahl, die über Ihre Rechnung entscheidet, und genau die schreibt niemand auf eine Launch-Folie.

And if you are simply trying to work out what "G​emini 3.8 TTS" costs — the answer is $9.00 per million audio tokens, on one of the two models that name refers to, until the end of 2026.

Nichts davon ist hypothetisch: Die dokumentierten KI-Ausfälle und Agent-Vorfälle, die hinter Releases wie diesem stehen, finden sich im OrcaRouter AI Incident Archive, wo jeder Eintrag seine eigenen Quellen, seinen Schweregrad, seinen Konfidenzgrad und sein Umstritten-Flag führt.