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Text Generation

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Gemini 2.5 Flash Lite API

Google Gemini 2.5 Flash Lite is an ultra-low-cost, low-latency model for classification, extraction, assistants, and high-frequency background tasks.

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Gemini 2.5 Flash Lite

Model:

gemini-2.5-flash-lite
Price: 0.2 credits per 1K input tokens · ≈ $0.0001-$0.0002 · 0.3 credits per 1K output tokens · ≈ $0.0001-$0.0003High stability with detailed usage records on the APIAny platform.
PlaygroundHistoryPricingModel overviewUse casesAPIFAQ
gemini-2.5-flash-lite
113 (suggested: 2,000)
0.7
02

Sampling temperature.

4096
165536

Maximum output tokens.

->

USD estimate $0.001-$0.002: highest recharge package uses $1 = 2,000 credits; entry package uses $1 = 1,000 credits.

Preview
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Gemini 2.5 Flash Lite
LLMResult preview

History

Saved locally in this browser

0 running · 0 completed

Your generation history will appear here

Input

0.2 credits/1K

≈ $0.0001-$0.0002

Output

0.3 credits/1K

≈ $0.0001-$0.0003

Cache

0.02 credits/1K

≈ $0.00001-$0.00002

Context

1M

Max output

66k
View API usage
Pricing
Model ID
Type
Quality
Price
gemini-2.5-flash-lite
Text Generation
Input tokens
0.2 credits per 1K input tokens · ≈ $0.0001-$0.0002
gemini-2.5-flash-lite
Text Generation
Cache read tokens
0.02 credits per 1K cached input tokens · ≈ $0.00001-$0.00002
gemini-2.5-flash-lite
Text Generation
Output tokens
0.3 credits per 1K output tokens · ≈ $0.0001-$0.0003
gemini-2.5-flash-lite
Text Generation
Minimum request
0.02 credits minimum · ≈ $0.000012-$0.000024
Model IDgemini-2.5-flash-lite
TypeText Generation
QualityInput tokens
Price0.2 credits per 1K input tokens · ≈ $0.0001-$0.0002
Model IDgemini-2.5-flash-lite
TypeText Generation
QualityCache read tokens
Price0.02 credits per 1K cached input tokens · ≈ $0.00001-$0.00002
Model IDgemini-2.5-flash-lite
TypeText Generation
QualityOutput tokens
Price0.3 credits per 1K output tokens · ≈ $0.0001-$0.0003
Model IDgemini-2.5-flash-lite
TypeText Generation
QualityMinimum request
Price0.02 credits minimum · ≈ $0.000012-$0.000024

Model overview

What is the Gemini 2.5 Flash Lite API?

Google Gemini 2.5 Flash Lite is an ultra-low-cost, low-latency model for classification, extraction, assistants, and high-frequency background tasks.

Measure throughput, latency, review effort, and unit economics against the operating target this model supports.

APIAny exposes Gemini 2.5 Flash Lite through one documented API surface with live pricing, model status, request examples, and an on-page playground. Teams can evaluate the model here, then keep authentication, usage records, and production routing in the same platform.

Try Gemini 2.5 Flash Lite in the playground
Gemini 2.5 Flash Lite API workflow overview on APIAny
A visual map of the Gemini 2.5 Flash Lite workflow.

APIAny advantages

Why use Gemini 2.5 Flash Lite through APIAny?

APIAny combines direct model access with the operational controls needed to move from evaluation to production without maintaining a separate integration for every provider.

Gemini 2.5 Flash Lite production benefits and operational value
Production value delivered by Gemini 2.5 Flash Lite.

One stable API surface

Call Gemini 2.5 Flash Lite with an APIAny key and a documented request format. Keep your application integration stable while model versions and upstream routes evolve behind the gateway.

Transparent usage and pricing

Review the live Gemini 2.5 Flash Lite pricing rules before a request, estimate credits in the playground, and inspect request-level usage records after the call completes.

Production routing controls

Use model status, channel health, retry policy, and usage logs to operate Gemini 2.5 Flash Lite as part of a production workflow instead of treating it as an isolated demo.

Use cases

What can you build with the Gemini 2.5 Flash Lite API?

These workflows show where Gemini 2.5 Flash Lite fits in a real product. Test the same inputs in the playground, compare the output with related models, and choose the route that meets your quality, latency, and budget requirements.

01

Classification and structured extraction

Turn messages and documents into labels, fields, or JSON with Gemini 2.5 Flash Lite. Define a strict output schema and validate results before automated downstream actions.

Try Gemini 2.5 Flash Lite in the playground
Gemini 2.5 Flash Lite API example for Classification and structured extraction
Classification and structured extraction with Gemini 2.5 Flash Lite.

02

Customer support assistants

Use Gemini 2.5 Flash Lite for support classification, answer drafting, self-service guidance, and multilingual conversations. Combine retrieval and policy checks so responses stay grounded in current product information.

Try Gemini 2.5 Flash Lite in the playground
Gemini 2.5 Flash Lite API example for Customer support assistants
Customer support assistants with Gemini 2.5 Flash Lite.

03

Tool-connected workflow automation

Use Gemini 2.5 Flash Lite to classify tasks, select tools, prepare structured arguments, and summarize results inside a larger workflow. Keep permissions and action validation outside the model boundary.

Try Gemini 2.5 Flash Lite in the playground
Gemini 2.5 Flash Lite API example for Tool-connected workflow automation
Tool-connected workflow automation with Gemini 2.5 Flash Lite.

Integration

How to integrate the Gemini 2.5 Flash Lite API

Move from a playground test to an authenticated production request in three steps. The page keeps the model identifier, request schema, pricing, and response examples together. Deploy with bounded inputs, observable task states, and clear escalation or fallback paths.

Gemini 2.5 Flash Lite API integration from request to output
Connecting Gemini 2.5 Flash Lite from API request to result.
  1. 01

    Create an API key

    Sign in to APIAny, create a project API key, and assign only the model scope and budget controls your application needs.

  2. 02

    Send a Gemini 2.5 Flash Lite request

    Copy the request example from this page, set the model field to the selected Gemini 2.5 Flash Lite version, and send it to the documented APIAny endpoint.

  3. 03

    Monitor and refine

    Track status, latency, credits, and returned usage. Compare versions or related models with the same workload before shifting production traffic.

Core capabilities

Key Gemini 2.5 Flash Lite API features

The following capabilities explain the practical input, output, and workflow characteristics that matter when evaluating Gemini 2.5 Flash Lite. Available request parameters remain visible in the live API reference on this page.

Gemini 2.5 Flash Lite capabilities and technical workflow
How Gemini 2.5 Flash Lite capabilities work together.

/01

Low-latency execution

Use the faster Gemini 2.5 Flash Lite route for interactive experiences, rapid iteration, and workloads where response time matters.

/02

Cost-efficient scaling

Run higher-volume Gemini 2.5 Flash Lite workloads while using live pricing and request-level usage records to control spend.

/03

Long-context processing

Use a large context window for codebases, documents, conversation history, and multi-step instructions while monitoring token cost.

/04

Multimodal understanding

Combine supported text and visual inputs so Gemini 2.5 Flash Lite can reason over more than one content format in the same workflow.

/05

Streaming responses

Render supported Gemini 2.5 Flash Lite text output incrementally for interactive assistants and long-running generation tasks.

SourceGoogle official documentation

ProviderGoogle

Reviewed2026-07-20

FAQ

Gemini 2.5 Flash Lite API frequently asked questions

Direct answers about capabilities, use cases, integration, and choosing the right Gemini 2.5 Flash Lite route.

What is the Gemini 2.5 Flash Lite API?

Google Gemini 2.5 Flash Lite is an ultra-low-cost, low-latency model for classification, extraction, assistants, and high-frequency background tasks. APIAny makes this model callable through an authenticated API with live pricing, status information, request examples, and a browser playground on the same page.

What can I build with the Gemini 2.5 Flash Lite API?

Common Gemini 2.5 Flash Lite workflows include Classification and structured extraction, Customer support assistants, Tool-connected workflow automation. The best fit depends on the input format, output quality, latency, and cost your product requires.

How do I call Gemini 2.5 Flash Lite through APIAny?

Create an APIAny key, use the endpoint documented on this page, and set the request model field to the selected Gemini 2.5 Flash Lite version. The playground can generate a working payload before you integrate it into application code.

How should I choose a Gemini 2.5 Flash Lite version?

Compare the versions shown on this page by price, supported parameters, and capabilities such as Low-latency execution, Cost-efficient scaling, Long-context processing. Test a representative production input before choosing the default route.

API Reference

Call this model through a standard REST API. Authenticate with your API key, then pick an endpoint below to see its parameters and examples.

Authentication

Every request needs a Bearer token in the Authorization header. Create an API key in the console.

Authorization: Bearer YOUR_API_KEY
POSThttps://apiany.ai/v1/chat/completions

Request parameters

ParameterTypeRequiredNotes
modelstringRequiredModel identifier to invoke. Use this model's ID.
messagesarrayRequiredConversation history in OpenAI chat format (role + content).
streambooleanOptionalWhen true, the response streams back as server-sent events.

Request example

curl "https://apiany.ai/v1/chat/completions" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "gemini-2.5-flash-lite",
  "messages": [
    {
      "role": "user",
      "content": "Summarize APIAny.AI's multi-channel model aggregation in three sentences, and give one production recommendation."
    }
  ],
  "temperature": 0.7,
  "max_tokens": 4096
}'

Response example

{
  "id": "chatcmpl-abc123",
  "object": "chat.completion",
  "model": "gemini-2.5-flash-lite",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Hello! How can I help?"
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 12,
    "completion_tokens": 18,
    "total_tokens": 30
  }
}

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