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Gemini 2.5 Flash

Up to 30%

Gemini 2.5 Flash brings Google speech-to-text to LLM.API for voice notes, calls, and caption pipelines.

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What is Gemini 2.5 Flash?

Gemini 2.5 Flash is a speech-to-text model on LLM.API (`gemini-2.5-flash`). gemini-2.5-flash provided by google-ai-studio, google-vertex. It is wired for API access through LLM.API with OpenAI-compatible patterns. Feed text, image, audio and receive text transcripts for captions, agents, and searchable archives.

Providers

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

List price by provider ($ / 1M tokens)

InputOutput
google-ai-studio$0.3 in
$2.5 out
google-vertex$0.3 in
$2.5 out

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

ProviderPricingContextCapabilities
google-ai-studio30% offin $300; out $2500 per 1M tokens1M tokensvision, tools, streaming, reasoning, JSON
google-vertex30% offin $300; out $2500 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 Flash right here — free to start.

Gemini 2.5 Flash
Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call Gemini 2.5 Flash 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-flash",
    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-flash",
  "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. Reflects Google positioning for this endpoint.

  • Downstream LLM prep

    Feeds transcripts into summarization and action-item extractors. 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.

  • Meeting capture

    Fits voice notes, calls, and meeting recording pipelines. Relevant for `gemini-2.5-flash` workloads on LLM.API.

  • Streaming recognition

    Supports low-latency partial transcripts when the provider offers streaming STT. Relevant for `gemini-2.5-flash` workloads on LLM.API.

6 Most Valuable Use Cases

  • Podcast and video caption drafts with Gemini 2.5 Flash
  • Call-center transcription and QA
  • Voice command capture in mobile apps with Gemini 2.5 Flash
  • Meeting notes and searchable recordings
  • Compliance recording text archives with Gemini 2.5 Flash
  • 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 Flash on LLM.API?

  • Unified AI Routing

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

  • Cost Control

    Compare provider price points and keep spend visible as you scale Gemini 2.5 Flash.

  • Reliability Layer

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

  • Observability

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

  • Drop-in SDKs

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

  • Model Breadth

    Swap Gemini 2.5 Flash 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 Flash)
  • Voice is a primary input modality in your product (Gemini 2.5 Flash)
  • You will pipe transcripts into search or LLM summarization (Gemini 2.5 Flash)

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 Flash benchmark scores

Intelligence index

This model10.
Tracked median8.

Scale: 0-100 index points

Output speed

This model188 t/s

Scale: 0-400 tokens per second

Reference price per 1M tokens

Input$0.30
Output$2.50

Bars compare input and output list prices for this model.

Artificial Analysis Intelligence Index10
Median index across all tracked models8
Output speed188 tokens/s
Reference input price$0.30 / 1M tokens
Reference output price$2.50 / 1M tokens

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

RELIABILITY

Gemini 2.5 Flash 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 Flash.

  • 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

  • What modalities does Gemini 2.5 Flash support?

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

  • How do I call Gemini 2.5 Flash via API?

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

  • Which providers serve Gemini 2.5 Flash?

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

  • What are limitations of Gemini 2.5 Flash?

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

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

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

  • When should I choose Gemini 2.5 Flash?

    You need speech-to-text for batch or streaming audio — especially when you specifically need Gemini 2.5 Flash.

  • What is the context length for Gemini 2.5 Flash?

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

  • Is Gemini 2.5 Flash a chat model?

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

  • What is Gemini 2.5 Flash?

    gemini-2.5-flash 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-flash`.

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