> ## Documentation Index
> Fetch the complete documentation index at: https://docs.apimart.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Gemini-3.1-Flash-Lite-Image (Nano Banana Lite) Image Generation

>  - The fastest and cheapest image model in the Gemini 3.1 family, designed for large-scale, low-cost image generation
- Supports 1K resolution only (passing 2K/4K/0.5K is automatically downgraded to 1K without an error)
- Supports text-to-image and image-to-image, up to 14 reference images
- Billed by input / output tokens; connects directly to the official Gemini channel, with asynchronous task-based image generation 

<RequestExample>
  ```bash cURL theme={null}
  curl --request POST \
    --url https://api.apimart.ai/v1/images/generations \
    --header 'Authorization: Bearer <token>' \
    --header 'Content-Type: application/json' \
    --data '{
      "model": "gemini-3.1-flash-lite-image",
      "prompt": "赛博朋克风格的城市夜景，霓虹灯闪烁",
      "size": "16:9",
      "resolution": "1K",
      "n": 1
    }'
  ```

  ```python Python theme={null}
  import requests

  url = "https://api.apimart.ai/v1/images/generations"

  payload = {
      "model": "gemini-3.1-flash-lite-image",
      "prompt": "赛博朋克风格的城市夜景，霓虹灯闪烁",
      "size": "16:9",
      "resolution": "1K",
      "n": 1
  }

  headers = {
      "Authorization": "Bearer <token>",
      "Content-Type": "application/json"
  }

  response = requests.post(url, json=payload, headers=headers)

  print(response.json())
  ```

  ```javascript JavaScript theme={null}
  const url = "https://api.apimart.ai/v1/images/generations";

  const payload = {
    model: "gemini-3.1-flash-lite-image",
    prompt: "赛博朋克风格的城市夜景，霓虹灯闪烁",
    size: "16:9",
    resolution: "1K",
    n: 1
  };

  const headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
  };

  fetch(url, {
    method: "POST",
    headers: headers,
    body: JSON.stringify(payload)
  })
    .then(response => response.json())
    .then(data => console.log(data))
    .catch(error => console.error('Error:', error));
  ```

  ```go Go theme={null}
  package main

  import (
      "bytes"
      "encoding/json"
      "fmt"
      "io/ioutil"
      "net/http"
  )

  func main() {
      url := "https://api.apimart.ai/v1/images/generations"

      payload := map[string]interface{}{
          "model":      "gemini-3.1-flash-lite-image",
          "prompt":     "赛博朋克风格的城市夜景，霓虹灯闪烁",
          "size":       "16:9",
          "resolution": "1K",
          "n":          1,
      }

      jsonData, _ := json.Marshal(payload)

      req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
      req.Header.Set("Authorization", "Bearer <token>")
      req.Header.Set("Content-Type", "application/json")

      client := &http.Client{}
      resp, err := client.Do(req)
      if err != nil {
          panic(err)
      }
      defer resp.Body.Close()

      body, _ := ioutil.ReadAll(resp.Body)
      fmt.Println(string(body))
  }
  ```

  ```java Java theme={null}
  import java.net.http.HttpClient;
  import java.net.http.HttpRequest;
  import java.net.http.HttpResponse;
  import java.net.URI;

  public class Main {
      public static void main(String[] args) throws Exception {
          String url = "https://api.apimart.ai/v1/images/generations";

          String payload = """
          {
            "model": "gemini-3.1-flash-lite-image",
            "prompt": "赛博朋克风格的城市夜景，霓虹灯闪烁",
            "size": "16:9",
            "resolution": "1K",
            "n": 1
          }
          """;

          HttpClient client = HttpClient.newHttpClient();
          HttpRequest request = HttpRequest.newBuilder()
              .uri(URI.create(url))
              .header("Authorization", "Bearer <token>")
              .header("Content-Type", "application/json")
              .POST(HttpRequest.BodyPublishers.ofString(payload))
              .build();

          HttpResponse<String> response = client.send(request,
              HttpResponse.BodyHandlers.ofString());

          System.out.println(response.body());
      }
  }
  ```

  ```php PHP theme={null}
  <?php

  $url = "https://api.apimart.ai/v1/images/generations";

  $payload = [
      "model" => "gemini-3.1-flash-lite-image",
      "prompt" => "赛博朋克风格的城市夜景，霓虹灯闪烁",
      "size" => "16:9",
      "resolution" => "1K",
      "n" => 1
  ];

  $ch = curl_init($url);
  curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
  curl_setopt($ch, CURLOPT_POST, true);
  curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload));
  curl_setopt($ch, CURLOPT_HTTPHEADER, [
      "Authorization: Bearer <token>",
      "Content-Type: application/json"
  ]);

  $response = curl_exec($ch);
  curl_close($ch);

  echo $response;
  ?>
  ```

  ```ruby Ruby theme={null}
  require 'net/http'
  require 'json'
  require 'uri'

  url = URI("https://api.apimart.ai/v1/images/generations")

  payload = {
    model: "gemini-3.1-flash-lite-image",
    prompt: "赛博朋克风格的城市夜景，霓虹灯闪烁",
    size: "16:9",
    resolution: "1K",
    n: 1
  }

  http = Net::HTTP.new(url.host, url.port)
  http.use_ssl = true

  request = Net::HTTP::Post.new(url)
  request["Authorization"] = "Bearer <token>"
  request["Content-Type"] = "application/json"
  request.body = payload.to_json

  response = http.request(request)
  puts response.body
  ```

  ```swift Swift theme={null}
  import Foundation

  let url = URL(string: "https://api.apimart.ai/v1/images/generations")!

  let payload: [String: Any] = [
      "model": "gemini-3.1-flash-lite-image",
      "prompt": "赛博朋克风格的城市夜景，霓虹灯闪烁",
      "size": "16:9",
      "resolution": "1K",
      "n": 1
  ]

  var request = URLRequest(url: url)
  request.httpMethod = "POST"
  request.setValue("Bearer <token>", forHTTPHeaderField: "Authorization")
  request.setValue("application/json", forHTTPHeaderField: "Content-Type")
  request.httpBody = try? JSONSerialization.data(withJSONObject: payload)

  let task = URLSession.shared.dataTask(with: request) { data, response, error in
      if let error = error {
          print("Error: \(error)")
          return
      }

      if let data = data, let responseString = String(data: data, encoding: .utf8) {
          print(responseString)
      }
  }

  task.resume()
  ```

  ```csharp C# theme={null}
  using System;
  using System.Net.Http;
  using System.Text;
  using System.Threading.Tasks;

  class Program
  {
      static async Task Main(string[] args)
      {
          var url = "https://api.apimart.ai/v1/images/generations";

          var payload = @"{
              ""model"": ""gemini-3.1-flash-lite-image"",
              ""prompt"": ""赛博朋克风格的城市夜景，霓虹灯闪烁"",
              ""size"": ""16:9"",
              ""resolution"": ""1K"",
              ""n"": 1
          }";

          using var client = new HttpClient();
          client.DefaultRequestHeaders.Add("Authorization", "Bearer <token>");

          var content = new StringContent(payload, Encoding.UTF8, "application/json");
          var response = await client.PostAsync(url, content);
          var result = await response.Content.ReadAsStringAsync();

          Console.WriteLine(result);
      }
  }
  ```

  ```c C theme={null}
  #include <stdio.h>
  #include <curl/curl.h>

  int main(void) {
      CURL *curl;
      CURLcode res;

      curl_global_init(CURL_GLOBAL_DEFAULT);
      curl = curl_easy_init();

      if(curl) {
          const char *url = "https://api.apimart.ai/v1/images/generations";
          const char *payload = "{"
              "\"model\":\"gemini-3.1-flash-lite-image\","
              "\"prompt\":\"赛博朋克风格的城市夜景，霓虹灯闪烁\","
              "\"size\":\"16:9\","
              "\"resolution\":\"1K\","
              "\"n\":1"
          "}";

          struct curl_slist *headers = NULL;
          headers = curl_slist_append(headers, "Authorization: Bearer <token>");
          headers = curl_slist_append(headers, "Content-Type: application/json");

          curl_easy_setopt(curl, CURLOPT_URL, url);
          curl_easy_setopt(curl, CURLOPT_POSTFIELDS, payload);
          curl_easy_setopt(curl, CURLOPT_HTTPHEADER, headers);

          res = curl_easy_perform(curl);

          if(res != CURLE_OK) {
              fprintf(stderr, "curl_easy_perform() failed: %s\n",
                      curl_easy_strerror(res));
          }

          curl_slist_free_all(headers);
          curl_easy_cleanup(curl);
      }

      curl_global_cleanup();
      return 0;
  }
  ```

  ```objectivec Objective-C theme={null}
  #import <Foundation/Foundation.h>

  int main(int argc, const char * argv[]) {
      @autoreleasepool {
          NSURL *url = [NSURL URLWithString:@"https://api.apimart.ai/v1/images/generations"];

          NSDictionary *payload = @{
              @"model": @"gemini-3.1-flash-lite-image",
              @"prompt": @"赛博朋克风格的城市夜景，霓虹灯闪烁",
              @"size": @"16:9",
              @"resolution": @"1K",
              @"n": @1
          };

          NSError *error;
          NSData *jsonData = [NSJSONSerialization dataWithJSONObject:payload
                                                            options:0
                                                              error:&error];

          NSMutableURLRequest *request = [NSMutableURLRequest requestWithURL:url];
          [request setHTTPMethod:@"POST"];
          [request setValue:@"Bearer <token>" forHTTPHeaderField:@"Authorization"];
          [request setValue:@"application/json" forHTTPHeaderField:@"Content-Type"];
          [request setHTTPBody:jsonData];

          NSURLSessionDataTask *task = [[NSURLSession sharedSession]
              dataTaskWithRequest:request
              completionHandler:^(NSData *data, NSURLResponse *response, NSError *error) {
                  if (error) {
                      NSLog(@"Error: %@", error);
                      return;
                  }
                  NSString *result = [[NSString alloc] initWithData:data
                                                          encoding:NSUTF8StringEncoding];
                  NSLog(@"%@", result);
              }];

          [task resume];
          [[NSRunLoop mainRunLoop] run];
      }
      return 0;
  }
  ```

  ```ocaml OCaml theme={null}
  (* Requires cohttp and yojson libraries *)
  open Lwt
  open Cohttp
  open Cohttp_lwt_unix

  let url = "https://api.apimart.ai/v1/images/generations"

  let payload = {|{
    "model": "gemini-3.1-flash-lite-image",
    "prompt": "赛博朋克风格的城市夜景，霓虹灯闪烁",
    "size": "16:9",
    "resolution": "1K",
    "n": 1
  }|}

  let () =
    let headers = Header.init ()
      |> fun h -> Header.add h "Authorization" "Bearer <token>"
      |> fun h -> Header.add h "Content-Type" "application/json"
    in
    let body = Cohttp_lwt.Body.of_string payload in

    let response = Client.post ~headers ~body (Uri.of_string url) >>= fun (resp, body) ->
      body |> Cohttp_lwt.Body.to_string >|= fun body_str ->
      print_endline body_str
    in
    Lwt_main.run response
  ```

  ```dart Dart theme={null}
  import 'dart:convert';
  import 'package:http/http.dart' as http;

  void main() async {
    final url = Uri.parse('https://api.apimart.ai/v1/images/generations');

    final payload = {
      'model': 'gemini-3.1-flash-lite-image',
      'prompt': '赛博朋克风格的城市夜景，霓虹灯闪烁',
      'size': '16:9',
      'resolution': '1K',
      'n': 1
    };

    final response = await http.post(
      url,
      headers: {
        'Authorization': 'Bearer <token>',
        'Content-Type': 'application/json',
      },
      body: jsonEncode(payload),
    );

    print(response.body);
  }
  ```

  ```r R theme={null}
  library(httr)
  library(jsonlite)

  url <- "https://api.apimart.ai/v1/images/generations"

  payload <- list(
    model = "gemini-3.1-flash-lite-image",
    prompt = "赛博朋克风格的城市夜景，霓虹灯闪烁",
    size = "16:9",
    resolution = "1K",
    n = 1
  )

  response <- POST(
    url,
    add_headers(
      Authorization = "Bearer <token>",
      `Content-Type` = "application/json"
    ),
    body = toJSON(payload, auto_unbox = TRUE),
    encode = "raw"
  )

  cat(content(response, "text"))
  ```
</RequestExample>

<ResponseExample>
  ```json 200 theme={null}
  {
    "code": 200,
    "data": [
      {
        "status": "submitted",
        "task_id": "task_01K8SGYNNNVBQTXNR4MM964S7K"
      }
    ]
  }
  ```

  ```json 400 theme={null}
  {
    "error": {
      "code": 400,
      "message": "请求参数无效",
      "type": "invalid_request_error"
    }
  }
  ```

  ```json 401 theme={null}
  {
    "error": {
      "code": 401,
      "message": "身份验证失败，请检查您的API密钥",
      "type": "authentication_error"
    }
  }
  ```

  ```json 402 theme={null}
  {
    "error": {
      "code": 402,
      "message": "账户余额不足，请充值后再试",
      "type": "payment_required"
    }
  }
  ```

  ```json 403 theme={null}
  {
    "error": {
      "code": 403,
      "message": "访问被禁止，您没有权限访问此资源",
      "type": "permission_error"
    }
  }
  ```

  ```json 429 theme={null}
  {
    "error": {
      "code": 429,
      "message": "请求过于频繁，请稍后再试",
      "type": "rate_limit_error"
    }
  }
  ```

  ```json 500 theme={null}
  {
    "error": {
      "code": 500,
      "message": "服务器内部错误，请稍后重试",
      "type": "server_error"
    }
  }
  ```

  ```json 502 theme={null}
  {
    "error": {
      "code": 502,
      "message": "网关错误，服务器暂时不可用",
      "type": "bad_gateway"
    }
  }
  ```
</ResponseExample>

## Authorizations

<ParamField header="Authorization" type="string" required>
  All API endpoints require Bearer Token authentication

  Get your API Key:

  Visit the [API Key Management Page](https://apimart.ai/keys) to get your API Key

  Add it to the request header:

  ```
  Authorization: Bearer YOUR_API_KEY
  ```
</ParamField>

## Body

<ParamField body="model" type="string" default="gemini-3.1-flash-lite-image" required>
  Image generation model name

  The following model names are supported:

  * `gemini-3.1-flash-lite-image` (Nano Banana Lite)
  * `gemini-3.1-flash-lite-image-ext`

  <Note>
    Both share the same parameters and constraints (1K only, `google_search` / `official_fallback` not supported, up to 14 reference images). Neither has a `-official` variant, and neither supports the `official_fallback` fallback parameter. Billing is subject to the backend configuration of each channel.
  </Note>
</ParamField>

<ParamField body="prompt" type="string" required>
  Text description for image generation
</ParamField>

<ParamField body="size" type="string">
  Image aspect ratio

  Supported ratios:

  * `auto` - Automatically choose the aspect ratio
  * `1:1` - Square, avatars, social media
  * `3:2` / `2:3` - Standard photos
  * `4:3` / `3:4` - Traditional display ratio
  * `16:9` / `9:16` - Widescreen / vertical video covers
  * `5:4` / `4:5` - Instagram images
  * `21:9` - Ultra-wide banner

  <Warning>
    For text-to-image, when `size` is `auto`, the default is `1:1` or `16:9`; for image-to-image, the aspect ratio follows the upstream response. (We recommend specifying an aspect ratio.)
  </Warning>
</ParamField>

<ParamField body="resolution" type="string" default="1K">
  Output image resolution

  Supported values:

  * `1K` - \~1024px, standard resolution (**the only tier Lite supports**)

  <Warning>
    **Lite only supports 1K**. Passing `2K` / `4K` / `0.5K` is **silently downgraded to 1K** — it won't raise an error, nor will it actually output higher resolution. The frontend UI does not need to expose a resolution option.
  </Warning>
</ParamField>

<ParamField body="n" type="integer" default="1">
  Number of images to generate

  Range: 1 to 4, default `1`

  When `n>1`, the backend sends multiple concurrent requests upstream and bills by the **actual number of successful images**. **We recommend the frontend always send 1** (to show progress image by image and make billing more intuitive).

  **⚠️ Note:** Must enter a plain number (e.g., `1`), do not use quotes or it will cause an error
</ParamField>

<ParamField body="image_urls" type="array">
  Reference image URL list for image-to-image generation

  Two formats are supported:

  **1. Full image URL**

  * Publicly accessible image URL (http\:// or https\://)
  * Example: `https://example.com/image.jpg`

  **2. Base64 encoded format**

  * **Must use the full Data URI format**
  * Format: `data:image/{format};base64,{base64data}`
  * Supported image formats: jpeg, png, webp
  * Example: `data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAYABg...`
  * ⚠️ Note: Must include the `data:image/jpeg;base64,` prefix

  **Limitations:**

  * Maximum **14** reference images (recommended: up to 10 object refs + 4 character refs)
  * Single image size: not exceeding 10MB
  * Supported formats: jpeg, png, webp
</ParamField>

<ParamField body="webhook" type="string">
  Task callback URL (base)

  When a task succeeds / fails, the platform calls back to `webhook + /callback` (it does not forward the upstream request). Passing this parameter can significantly reduce polling; we still recommend keeping polling as a fallback.
</ParamField>

<Note>
  **Lite usage notes**

  * **`google_search` / `google_image_search` are not supported**: Lite uses the Developer API's `interactions` endpoint, and the upstream has not enabled the Search tool (it returns "Search as tool is not enabled for this model"), so the platform adapter does not send this parameter either. **Passing it won't raise an error and images are generated as usual, but there is no search enhancement effect at all**. If you need search enhancement, switch to `gemini-3.1-flash-image-preview`.
  * `mask_url` inpainting is not supported (the Gemini family uses aspect ratio + reference images rather than masks).
  * **Billed by token** (unlike the fixed per-image price of flash/pro): input is about $0.25 per million tokens, image output is about $30 per million tokens, and a single 1K image ≈ 1120 output tokens ≈ **\$0.0336/image**. The actual price is subject to the backend multiplier configuration.
  * All generated images contain Google's **SynthID** invisible watermark (upstream behavior, cannot be disabled).
</Note>

## Response

<ResponseField name="code" type="integer">
  Response status code
</ResponseField>

<ResponseField name="data" type="array">
  Response data array

  <Expandable title="Properties">
    <ResponseField name="status" type="string">
      Task status

      * `submitted` - Submitted
    </ResponseField>

    <ResponseField name="task_id" type="string">
      Unique task identifier
    </ResponseField>
  </Expandable>
</ResponseField>