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Gemini 2.5 Pro

Up to 30%

Transcribe speech with Gemini 2.5 Pro on LLM.API—batch or streaming audio to text with the same developer surface as your other models.

Start Using API

What is Gemini 2.5 Pro?

With Gemini 2.5 Pro, LLM.API turns audio into text for product voice features. gemini-2.5-pro provided by google-ai-studio, google-vertex. It is wired for API access through LLM.API with OpenAI-compatible patterns. The model id `gemini-2.5-pro` keeps STT alongside your other endpoints.

Providers

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

List price by provider ($ / 1M tokens)

InputOutput
google-ai-studio$1.25 in
$10 out
google-vertex$1.25 in
$10 out

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

ProviderPricingContextCapabilities
google-ai-studio30% offin $1250; out — per 1M tokens1M tokensvision, tools, streaming, reasoning, JSON
google-vertex30% offin $1250; out — per 1M tokens1M tokensvision, tools, streaming, reasoning, JSON

Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 21 Sept 2026.

Try this model

Test Gemini 2.5 Pro right here — free to start.

Gemini 2.5 Pro
Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

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

python
from openai import OpenAI

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

resp = client.chat.completions.create(
    model="gemini-2.5-pro",
    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)
{
  "model": "gemini-2.5-pro",
  "messages": [
    {"role": "system", "content": "You are a precise product assistant."},
    {"role": "user", "content": "Give me three crisp launch checklist items."}
  ]
}

5 Core Capabilities

  • Compliance archives

    Creates text records of spoken interactions for audit trails. Tuned to how teams typically call Gemini 2.5 Pro.

  • Downstream LLM prep

    Feeds transcripts into summarization and action-item extractors. Reflects Google positioning for this endpoint.

  • Multilingual audio

    Handles diverse accents and languages depending on the model. Tuned to how teams typically call Gemini 2.5 Pro.

  • Caption generation

    Produces base transcripts for subtitle workflows. Reflects Google positioning for this endpoint.

  • Speech transcription

    Converts spoken audio into text for captions, notes, and search. Grounded in the model's stt role rather than generic chat claims.

6 Most Valuable Use Cases

  • Live captioning prototypes with Gemini 2.5 Pro
  • Meeting notes and searchable recordings
  • Clinical or field note dictation workflows with Gemini 2.5 Pro
  • Voice command capture in mobile apps
  • Compliance recording text archives with Gemini 2.5 Pro
  • Feeding voice input into LLM agents

Why Build on LLM.API?

One unified API. Every major model. Built-in reliability, cost control, and observability.

  • Intelligent AI Routing

    Automatically route each request to the best model across providers based on latency, cost, and quality—without changing your integration or redeploying code.

    One endpoint, every model.

  • Cost-Aware Execution

    Control spend with per-request cost estimation, smart model selection, and centralized quotas so teams can experiment fast without runaway bills or manual tracking.

    More performance, less spend.

  • Resilient Fallback Flows

    Define automatic, provider-agnostic fallbacks to keep your app up during outages, rate limits, or timeouts—no brittle failover logic scattered through your codebase.

    Never go dark on users.

  • Deep LLM Observability

    Trace every call across providers with logs, metrics, and request replay so you can debug, tune prompts, and optimize model choices from one unified dashboard.

    See every token, everywhere.

  • Task-Level Orchestration

    Describe tasks, not models. LLM.API maps them to the right tools, models, and prompts so you ship complex AI workflows with minimal glue code.

    Think tasks, not models.

  • High-Throughput Batch APIs

    Process millions of inferences efficiently with optimized batch pipelines, concurrency controls, and retry logic—all behind the same simple interface you use for single calls.

    Scale from 1 to millions.

Why run Gemini 2.5 Pro on LLM.API?

  • Unified AI Routing

    Production: Reach Gemini 2.5 Pro and sibling models through one OpenAI-compatible endpoint.

  • Cost Control

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

  • Reliability Layer

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

  • Observability

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

  • Drop-in SDKs

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

  • Model Breadth

    Swap Gemini 2.5 Pro for chat, media, or embedding alternatives without rewriting auth.

When to Use — When NOT to Use

Use it if...

  • You need speech-to-text for batch or streaming audio (Gemini 2.5 Pro)
  • You will pipe transcripts into search or LLM summarization (Gemini 2.5 Pro)
  • Voice is a primary input modality in your product (Gemini 2.5 Pro)

Avoid if...

  • You require guaranteed perfect transcripts for every accent without evaluation
  • You need text-to-speech or chat generation instead of transcription
  • Your audio cannot leave your compliance boundary and you lack an approved provider path

BENCHMARKS

Gemini 2.5 Pro benchmark scores

Intelligence index

This model17.
Tracked median24.

Scale: 0-100 index points

Output speed

This model121 t/s

Scale: 0-400 tokens per second

Reference price per 1M tokens

Input$1.25
Output$10.00

Bars compare input and output list prices for this model.

Artificial Analysis Intelligence Index17
Median index across all tracked models24
Output speed121 tokens/s
Reference input price$1.25 / 1M tokens
Reference output price$10.00 / 1M tokens

Independent scores published by Artificial Analysis (source). Reference prices are provider list prices, not LLM.API pricing.

RELIABILITY

Gemini 2.5 Pro 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.

COMMUNITY

What developers say about Gemini models

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 Pro.

  • The Flash line is praised for speed and cost — reviewers regularly report code generated in seconds where slower models take minutes.
  • The main caveat raised is confident hallucination on under-specified tasks, so reviewers recommend verification steps or a stronger model for critical output.
  • Community reports highlight good long-context handling and strong multimodal input as the reasons teams keep Flash in the loop despite the accuracy caveats.

SOURCES

Frequently Asked Questions

  • Is Gemini 2.5 Pro a chat model?

    No—Gemini 2.5 Pro is categorized as a stt model. Use the matching API surface rather than assuming chat completions.

  • What modalities does Gemini 2.5 Pro support?

    Gemini 2.5 Pro accepts text, image, audio and produces text according to its architecture metadata on LLM.API.

  • Can I use tools or structured outputs with Gemini 2.5 Pro?

    Tool and/or structured-output flags appear on one or more providers for this model—confirm in the providers table.

  • Does Gemini 2.5 Pro support streaming?

    Yes—at least one listed provider advertises streaming.

  • When should I choose Gemini 2.5 Pro?

    You will pipe transcripts into search or LLM summarization — especially when you specifically need Gemini 2.5 Pro.

  • How do I call Gemini 2.5 Pro via API?

    Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "gemini-2.5-pro" and your LLM.API key. See the code snippet on this page.

  • How is Gemini 2.5 Pro priced on LLM.API?

    Listed pricing metadata shows: In $1.25 / 1M tokens · Out $10.00 / 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.

  • What is the context length for Gemini 2.5 Pro?

    Reported context for Gemini 2.5 Pro is 1M tokens. Always verify the active provider row if multiple providers are listed.

  • Which providers serve Gemini 2.5 Pro?

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

  • Does Gemini 2.5 Pro translate speech?

    Primary behavior is transcription to text. Translation—if needed—should be a separate step with a chat model unless the provider explicitly offers it.

  • What are limitations of Gemini 2.5 Pro?

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

  • What is Gemini 2.5 Pro?

    gemini-2.5-pro provided by google-ai-studio, google-vertex. It is wired for API access through LLM.API with OpenAI-compatible patterns. On LLM.API it is addressed as `gemini-2.5-pro`.

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