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Gemini 2.5 Flash Preview TTS API: Endpoint & Pricing

Synthesize speech with Gemini 2.5 Flash Preview TTS on LLM.API—text in, audio out, billed and authenticated like the rest of your model fleet.

Start Using API

What is Gemini 2.5 Flash Preview TTS?

Gemini 2.5 Flash Preview TTS is a text-to-speech model on LLM.API (`gemini-2.5-flash-preview-tts`). Text-to-speech model by Google-Ai-Studio. It converts text into audio for assistants, narration, and accessibility.

Can you self-host Gemini 2.5 Flash Preview TTS?

No. We found no public weights for Gemini 2.5 Flash Preview TTS on Hugging Face, so there is nothing to download, quantize or serve on your own GPUs: no VRAM budget, no vLLM or GGUF build to plan for. The only way to run it is over an API.

Skip the deploy — use LLM.API as your endpoint

No GPUs, no quantization trade-offs. Same model, OpenAI-compatible, with custom volume discounts on request.

Get API keySee API code ↓

Providers

LLM.API routes Gemini 2.5 Flash Preview TTS to the providers below, with discounted effective rates versus list price.

List price by provider

InputOutput
google-ai-studio$0 in
$0 out

Provider list prices; the LLM.API discount applies on top.

ProviderPricingContextCapabilities
google-ai-studioin $0; out — per 1M characters——

Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 11 Oct 2026.

Try this model

Test Gemini 2.5 Flash Preview TTS right here — free to start.

Gemini 2.5 Flash Preview TTS
Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call Gemini 2.5 Flash Preview TTS through the OpenAI-compatible API — TTS via LLM.API (see docs for audio endpoints).

Switching from OpenAI? Change 2 lines.

- base_url="https://api.openai.com/v1"
- api_key="YOUR_OPENAI_KEY"
+ base_url="https://api.llmapi.ai/v1"
+ api_key="YOUR_LLMAPI_KEY"

Everything else stays the same — SDK, message format, tools, streaming. Set model to gemini-2.5-flash-preview-tts and the call runs unchanged.

bash
curl https://api.llmapi.ai/v1/chat/completions \
  -H "Authorization: Bearer $LLMAPI_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-2.5-flash-preview-tts",
    "messages": [
      {"role": "user", "content": "Give me three crisp launch checklist items."}
    ]
  }'
from openai import OpenAI

client = OpenAI(
    api_key="YOUR_LLMAPI_KEY",
    base_url="https://api.llmapi.ai/v1",
)

resp = client.chat.completions.create(
    model="gemini-2.5-flash-preview-tts",
    messages=[
        {"role": "system", "content": "You are a precise product assistant."},
        {"role": "user", "content": "Give me three crisp launch checklist items."},
    ],
)
print(resp.choices[0].message.content)
import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.LLMAPI_KEY,
  baseURL: "https://api.llmapi.ai/v1",
});

const resp = await client.chat.completions.create({
  model: "gemini-2.5-flash-preview-tts",
  messages: [
    { role: "user", content: "Give me three crisp launch checklist items." },
  ],
});

console.log(resp.choices[0].message.content);
stream = client.chat.completions.create(
    model="gemini-2.5-flash-preview-tts",
    messages=[{"role": "user", "content": "Write a haiku about latency."}],
    stream=True,
)

for chunk in stream:
    delta = chunk.choices[0].delta.content
    if delta:
        print(delta, end="", flush=True)
{
  "model": "gemini-2.5-flash-preview-tts",
  "messages": [
    {"role": "system", "content": "You are a precise product assistant."},
    {"role": "user", "content": "Give me three crisp launch checklist items."}
  ]
}

ENDPOINTS

Supported endpoints & features

Base URL https://api.llmapi.ai/v1 · model ID gemini-2.5-flash-preview-tts · OpenAI-compatible.

  • POST /v1/chat/completionsChat Completions — supported
FeatureStatusHow to set it
Function calling (tools)Not supportedtools, tool_choice
Parallel tool callsNot supportedparallel_tool_calls
JSON modeSupportedresponse_format: {"type": "json_object"}
Structured outputsNot supportedresponse_format: {"type": "json_schema", …}
StreamingNot supportedstream: true
Vision (image input)Not supportedimage_url content parts
Web searchNot supportedweb_search

ERRORS

Errors & fallback routing

CodeWhat it meansWhat to do
401Missing or invalid API key.Send Authorization: Bearer YOUR_LLMAPI_KEY and check the key is active.
429Rate limited, or the upstream provider is throttling the request.Back off and retry with jitter; the gateway also retries the request on another provider where one is available.
5xxUpstream provider error or timeout.Retry; fallback routing sends the retry to the next healthy provider for this model.

When a provider fails or throttles, the request is routed to the next provider serving this model — the ones listed in the providers table above.

Gemini 2.5 Flash Preview TTS in production

What the model is good at.

  • Multilingual voices

    Supports multiple languages where the provider catalog allows. Relevant for `gemini-2.5-flash-preview-tts` workloads on LLM.API.

  • Natural speech synthesis

    Turns text into spoken audio for assistants, accessibility, and media. Reflects text-to-speech positioning for this endpoint.

  • IVR and alerts

    Generates spoken prompts for support and notification flows. Tuned to how teams typically call Gemini 2.5 Flash Preview TTS.

  • Content narration

    Narrates articles, lessons, and product guides. Grounded in the model's tts role rather than generic chat claims.

  • Promptable delivery

    Responds to punctuation and phrasing cues for pacing. Relevant for `gemini-2.5-flash-preview-tts` workloads on LLM.API.

What you get when you call Gemini 2.5 Flash Preview TTS through LLM.API.

  • Unified AI Routing

    Practical: Reach Gemini 2.5 Flash Preview TTS and sibling models through one OpenAI-compatible endpoint.

    One endpoint, every model.

  • Cost Control

    Production: Compare provider price points and keep spend visible as you scale Gemini 2.5 Flash Preview TTS.

    More performance, less spend.

  • Reliability Layer

    Retry and route across configured providers when a single upstream blips.

    Never go dark on users.

  • Observability

    Trace prompts, tokens, and errors for Gemini 2.5 Flash Preview TTS alongside the rest of your stack.

    See every token, everywhere.

  • Drop-in SDKs

    Practical: Keep using familiar OpenAI client patterns with base URL https://api.llmapi.ai/v1.

    Think tasks, not models.

  • Model Breadth

    Production: Swap Gemini 2.5 Flash Preview TTS for chat, media, or embedding alternatives without rewriting auth.

    Scale from 1 to millions.

When to Use — When NOT to Use

Use it if...

  • Your UX requires spoken responses or narration (Gemini 2.5 Flash Preview TTS)
  • You need text-to-speech without managing voice infrastructure (Gemini 2.5 Flash Preview TTS)
  • You want API-driven voice prototypes that can go to production (Gemini 2.5 Flash Preview TTS)

Avoid if...

  • You need speech recognition rather than synthesis
  • You require a specific celebrity voice you do not have rights to
  • You only need embeddings or OCR

RELIABILITY

Gemini 2.5 Flash Preview TTS uptime, last 30 days

30-Day Uptime
100.00%
Past Incidents (30d)
0
Error rate (24h)
0.00%

Last 30 days

30/30 days operational | 100.00% uptime

Availability tracked for this model. Full history on the LLM Uptime Status page or the status hub. LLM.API routes around provider outages automatically.

LLM API rating for Gemini 2.5 Flash Preview TTS

★ 3.9/ 5.0LLM API rating
50% production adoption · 30% category benchmark · 20% tooling & valueEstimated from published specs
4.8Production adoptionVery high production volume
3.0Benchmark qualityScored on published audio support
3.0Developer ecosystemContext window, tool and JSON support, price against the category median
Voice & audio 3.9
How is this rating calculated?

Every model gets a separate 1.0–5.0 score for each category it can be used in, so a model can rate high for coding and lower for vision. The score combines three parts:

  1. Production adoption — 50%. How widely the model is actually used in production: provider traffic, LiteLLM and gateway usage, open-weight downloads and its LMArena rank. Proven, widely used models score highest.
  2. Category benchmark — 30%. The public benchmark that matters for that category — the Artificial Analysis Intelligence Index and LMArena Elo for reasoning, LMArena coding Elo for coding, image and document support plus vision Elo for vision, tool and JSON support for function calling, measured speed for voice.
  3. Tooling & value — 20%. Context window, support for tools, structured outputs and streaming, and price compared with the category median.

Scores of 4.0 and above are shown in green, 3.0–3.9 in yellow, below 3.0 in red. When a model has no public data for a part, it gets a neutral value instead of an invented number.

A “Verified benchmark” mark (✓) means an independent lab — LMArena or Artificial Analysis — has actually tested that model, and the source figure is shown. Models without that mark are labelled “Estimated from published specs”: the score comes from the published context window, tool and schema support, price and adoption only, because no independent lab has tested them yet.

One exception: a brand-new top-tier model that scores very high on the independent benchmarks but has no usage history yet is rated on the benchmark (60%) and tooling & value (40%) alone, so a missing adoption figure can't hold it back. All inputs come from public sources and are refreshed weekly.

Adoption and benchmark inputs come from public sources — LMArena, Artificial Analysis Intelligence Index and published model specs. Updated weekly.

COMMUNITY

What developers say about text-to-speech models

LMArena—Speed—Sources: LMArena, Artificial Analysis

Summarised from publicly published developer and community reviews of this model family. Opinions are the sources’, not LLM.API’s, and may not be specific to Gemini 2.5 Flash Preview TTS.

  • Community consensus still puts ElevenLabs-class voices at the top for realism and emotional range.
  • The debate has shifted from quality to value, as open-source voices mature and heavy usage pushes teams to higher tiers.
  • Developers advise designing for rate limits early — 429 handling on generation calls is a common production surprise.

SOURCES

Frequently Asked Questions

  • What modalities does Gemini 2.5 Flash Preview TTS support?

    Gemini 2.5 Flash Preview TTS accepts text and produces audio according to its architecture metadata on LLM.API.

  • How is Gemini 2.5 Flash Preview TTS priced on LLM.API?

    Listed pricing metadata shows: In $2.00 / 1M tokens. LLM.API may offer discounted effective rates (illustrative ~30% callout vs list when available).. Confirm live rates in the LLM.API dashboard or docs before production budgeting.

  • When should I choose Gemini 2.5 Flash Preview TTS?

    You need text-to-speech without managing voice infrastructure — especially when you specifically need Gemini 2.5 Flash Preview TTS.

  • Which providers serve Gemini 2.5 Flash Preview TTS?

    LLM.API currently lists: google-ai-studio. Availability can vary by region and account.

  • Can I use tools or structured outputs with Gemini 2.5 Flash Preview TTS?

    Tooling support varies; for pure tts models, prefer the modalities listed rather than assuming chat tools.

  • Does Gemini 2.5 Flash Preview TTS support streaming?

    Streaming depends on the active provider; check the providers table on this page for flags.

  • Where is the canonical page for Gemini 2.5 Flash Preview TTS?

    https://llmapi.ai/models/google-gemini-2-5-flash-preview-tts/

  • What are limitations of Gemini 2.5 Flash Preview TTS?

    Like other API models, Gemini 2.5 Flash Preview TTS can be wrong, incomplete, or uneven on edge cases. Validate outputs for high-stakes use. Media/OCR/STT models additionally depend on input quality.

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