gemini-2.5-flash Lite API

Gemini 2.5 Flash-Lite focuses on lightweight, high-volume tasks such as classification and data extraction, with cost and latency as its main design priorities.

MODALITIES

TextText

Temporarily unavailable

INPUT / OUTPUT75% OFF

$0.025/ 1M

$0.1/ 1M

USD per million tokens

CACHED INPUT

$0.0025/ 1M

Platform price · USD

CONTEXT WINDOW

128,000tokens

Max output: 16,384 tokens

gemini-2.5-flash Lite

API Usage Get API access

API Usage Examples

API documentation ↗

POSTGet API Key ↗

curl 'https://vip.astralgames.ai/v1beta/models/gemini-2.5-flash-lite:generateContent' \
  -H "Content-Type: application/json" \
  -H "x-goog-api-key: $MODEL_API_KEY" \
  --data '{
  "contents": [
    {
      "role": "user",
      "parts": [
        {
          "text": "Explain how an HTTP request works in three concise steps."
        }
      ]
    }
  ],
  "generationConfig": {
    "maxOutputTokens": 1024
  }
}'

const apiKey = process.env.MODEL_API_KEY;

const response = await fetch("https://vip.astralgames.ai/v1beta/models/gemini-2.5-flash-lite:generateContent", {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    "x-goog-api-key": apiKey
  },
  body: JSON.stringify({
    "contents": [
      {
        "role": "user",
        "parts": [
          {
            "text": "Explain how an HTTP request works in three concise steps."
          }
        ]
      }
    ],
    "generationConfig": {
      "maxOutputTokens": 1024
    }
  })
});

if (!response.ok) throw new Error(await response.text());
console.log(await response.text());

import os
import json
import requests

response = requests.post(
    "https://vip.astralgames.ai/v1beta/models/gemini-2.5-flash-lite:generateContent",
    headers={
        "Content-Type": "application/json",
        "x-goog-api-key": os.environ["MODEL_API_KEY"]
    },
    json=json.loads("{\"contents\":[{\"role\":\"user\",\"parts\":[{\"text\":\"Explain how an HTTP request works in three concise steps.\"}]}],\"generationConfig\":{\"maxOutputTokens\":1024}}"),
    timeout=300,
)
response.raise_for_status()
print(response.text)

curl 'https://vip.astralgames.ai/v1beta/models/gemini-2.5-flash-lite:streamGenerateContent?alt=sse' \
  -H "Content-Type: application/json" \
  -H "x-goog-api-key: $MODEL_API_KEY" \
  --data '{
  "contents": [
    {
      "role": "user",
      "parts": [
        {
          "text": "Explain how an HTTP request works in three concise steps."
        }
      ]
    }
  ],
  "generationConfig": {
    "maxOutputTokens": 1024
  }
}'

const apiKey = process.env.MODEL_API_KEY;

const response = await fetch("https://vip.astralgames.ai/v1beta/models/gemini-2.5-flash-lite:streamGenerateContent?alt=sse", {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    "x-goog-api-key": apiKey
  },
  body: JSON.stringify({
    "contents": [
      {
        "role": "user",
        "parts": [
          {
            "text": "Explain how an HTTP request works in three concise steps."
          }
        ]
      }
    ],
    "generationConfig": {
      "maxOutputTokens": 1024
    }
  })
});

if (!response.ok) throw new Error(await response.text());
console.log(await response.text());

import os
import json
import requests

response = requests.post(
    "https://vip.astralgames.ai/v1beta/models/gemini-2.5-flash-lite:streamGenerateContent?alt=sse",
    headers={
        "Content-Type": "application/json",
        "x-goog-api-key": os.environ["MODEL_API_KEY"]
    },
    json=json.loads("{\"contents\":[{\"role\":\"user\",\"parts\":[{\"text\":\"Explain how an HTTP request works in three concise steps.\"}]}],\"generationConfig\":{\"maxOutputTokens\":1024}}"),
    timeout=300,
)
response.raise_for_status()
print(response.text)

curl 'https://vip.astralgames.ai/v1/interactions' \
  -H "Content-Type: application/json" \
  -H "x-goog-api-key: $MODEL_API_KEY" \
  --data '{
  "model": "gemini-2.5-flash-lite",
  "input": "Explain how an HTTP request works in three concise steps.",
  "stream": false
}'

const apiKey = process.env.MODEL_API_KEY;

const response = await fetch("https://vip.astralgames.ai/v1/interactions", {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    "x-goog-api-key": apiKey
  },
  body: JSON.stringify({
    "model": "gemini-2.5-flash-lite",
    "input": "Explain how an HTTP request works in three concise steps.",
    "stream": false
  })
});

if (!response.ok) throw new Error(await response.text());
console.log(await response.text());

import os
import json
import requests

response = requests.post(
    "https://vip.astralgames.ai/v1/interactions",
    headers={
        "Content-Type": "application/json",
        "x-goog-api-key": os.environ["MODEL_API_KEY"]
    },
    json=json.loads("{\"model\":\"gemini-2.5-flash-lite\",\"input\":\"Explain how an HTTP request works in three concise steps.\",\"stream\":false}"),
    timeout=300,
)
response.raise_for_status()
print(response.text)

curl 'https://vip.astralgames.ai/v1beta/interactions' \
  -H "Content-Type: application/json" \
  -H "x-goog-api-key: $MODEL_API_KEY" \
  --data '{
  "model": "gemini-2.5-flash-lite",
  "input": "Explain how an HTTP request works in three concise steps.",
  "stream": false
}'

const apiKey = process.env.MODEL_API_KEY;

const response = await fetch("https://vip.astralgames.ai/v1beta/interactions", {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    "x-goog-api-key": apiKey
  },
  body: JSON.stringify({
    "model": "gemini-2.5-flash-lite",
    "input": "Explain how an HTTP request works in three concise steps.",
    "stream": false
  })
});

if (!response.ok) throw new Error(await response.text());
console.log(await response.text());

import os
import json
import requests

response = requests.post(
    "https://vip.astralgames.ai/v1beta/interactions",
    headers={
        "Content-Type": "application/json",
        "x-goog-api-key": os.environ["MODEL_API_KEY"]
    },
    json=json.loads("{\"model\":\"gemini-2.5-flash-lite\",\"input\":\"Explain how an HTTP request works in three concise steps.\",\"stream\":false}"),
    timeout=300,
)
response.raise_for_status()
print(response.text)

Set MODEL_API_KEY in your server environment. Requests use this model’s native API and your account pricing.

Docs: authentication and keys · Error handling

gemini-2.5-flash Lite pricing

Estimate one request, then choose a budget for your workflow.

Usage	Quantity	Rate	Cost
Input	tokens	$0.025/ 1M	$0.000025
Cached input	tokens	$0.0025/ 1M	$0
Output	tokens	$0.1/ 1M	$0.00005
Reasoning	tokens	$0.1/ 1M	$0

Cost per request$0.000075

Public USD estimate. Your account rate and final recorded usage determine the actual charge.

Model pricing details

Specification	Our price	Official reference
Input	$0.025 / 1M tokens	$0.1 About 75% less than official
Cached input	$0.0025 / 1M tokens	$0.01 About 75% less than official
Output	$0.1 / 1M tokens	$0.4 About 75% less than official
Reasoning	$0.1 / 1M tokens	$0.4 About 75% less than official

Related Models

All Models ↗

Model	Input / output	Cached input	Context	Input → output
gemini-2.5-flash LiteCurrentGoogle	$0.025 / $0.1per 1M tokens	$0.0025per 1M tokens	128,000	TextText
Claude Fable 5Same billing unitsAnthropic	$3 / $15per 1M tokens	$0.3per 1M tokens	1,000,000	TextText
Claude Fable 5.1Same billing unitsAnthropic	$3 / $15per 1M tokens	$0.075per 1M tokens	1,000,000	TextText
Claude Opus 4.6Same billing unitsAnthropic	$1.5 / $7.5per 1M tokens	$0.15per 1M tokens	1,000,000	TextText
Claude Opus 4.7Same billing unitsAnthropic	$1.5 / $7.5per 1M tokens	$0.15per 1M tokens	1,000,000	TextText
Claude Opus 4.8Same billing unitsAnthropic	$1.5 / $7.5per 1M tokens	$0.15per 1M tokens	1,000,000	TextText

gemini-2.5-flash Lite API · Examples

Original prompts adapted to documented capabilities; these are not vendor-generated outputs.

Official source ↗ · 2026-10-18

EXAMPLE PROMPT

Classify each feedback item as usability, reliability, billing or other. Include a short supporting quote and flag ambiguous items. Feedback: [paste text]

USER MESSAGE

Feedback classification

Apply explicit categories to a batch of short inputs.

EXAMPLE PROMPT

Extract the product, reported problem and requested action from each ticket. Return a JSON array; use null for missing facts. Tickets: [paste tickets]

USER MESSAGE

Support ticket extraction

Use a fixed output structure and preserve missing information.

What Is gemini-2.5-flash Lite?

Gemini 2.5 Flash-Lite focuses on lightweight, high-volume tasks such as classification and data extraction, with cost and latency as its main design priorities.

Official model information ↗ · 2026-10-18

gemini-2.5-flash Lite Platform specifications

Specification	gemini-2.5-flash Lite
Model ID	gemini-2.5-flash-lite
Provider	Google
API	/v1beta/models/{model}:generateContent · /v1beta/models/{model}:streamGenerateContent · /v1/interactions · /v1beta/interactions
Context window	128,000 tokens
Maximum output	16,384 tokens
Declared capabilities	See the native API contract

Protocol & capability details

Protocol & capabilities

gemini · gemini-2.5-flash-lite

Context limit: 128000
Maximum output: 16384

Compare gemini-2.5-flash Lite with related models

Specification	gemini-2.5-flash Lite	Claude Fable 5	Claude Fable 5.1
Provider	Google	Anthropic	Anthropic
Input → output	TextText	TextText	TextText
Selection basis	Current model	Same billing units	Same billing units
Context / max output	128,000 / 16,384	1,000,000 / 128,000	1,000,000 / 128,000
Starting price	$0.025 / 1M tokens	$3 / 1M tokens	$3 / 1M tokens

Choose by the input types, output settings and billing unit your workflow needs. Try the same prompt across models to compare results for your own use case.

Integrate gemini-2.5-flash Lite into your app

Keep the native request format and point your application to the platform API. Prepare a key with model access, then review status and charges in your usage records.

View API examples

gemini-2.5-flash Lite API · Common Questions

Everything you need to know about API access, pricing and model capabilities.

How is gemini-2.5-flash Lite billed?

Charges depend on the recorded token usage and your account rates. Input, output and supported cache or reasoning categories are listed separately in the pricing table. The calculator uses public USD prices; the final usage receipt determines the charge.

How do I get an API key?

Choose “Get API access” to open the integration guide. Sign in to your Astral Nexus account, prepare a key with access to this model and copy an API example.

Which API endpoints can I use?

Supported endpoints: /v1beta/models/{model}:generateContent、/v1beta/models/{model}:streamGenerateContent、/v1/interactions、/v1beta/interactions. Choose an endpoint in the API examples to see its native request format.

Does the model support streaming?

Streaming is not declared for the current route. Use the response format supported by its API.

Can I use tools or structured output?

Tools: not declared. Structured output: not declared. Request fields follow the selected native endpoint.

Where can I check usage and charges?

Keep the request ID and open your account’s LLM usage records to inspect request status, token counts and charges. Prompt and answer content are not a conversation history in this view.

Explore LLM Use Cases

All LLM models ↗

Feedback classification

Apply explicit categories to a batch of short inputs.

Explore ↗

Support ticket extraction

Use a fixed output structure and preserve missing information.

Explore ↗

Integration topics / Documentation

All documentation ↗

QUICK STARTHello, API.

Docs: Make your first API request

Prepare a key, choose a model and send a minimal request.

View docs section ↗

NATIVE API{ messages: [...] }

Docs: Use the native API

Explore request formats for OpenAI, Claude and Gemini.

View docs section ↗

INTEGRATIONbuild(something)

Docs: Evaluate real task cost

Separate token estimates, account pricing and final usage receipts.

View docs section ↗