# model kann "gemini-3.1-flash-lite-image" sein, ebenso kompatibel mit dem Alias "nano-banana-2-lite"
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
}'
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())
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));
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))
}
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
$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;
?>
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
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()
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);
}
}
#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;
}
#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;
}
(* 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
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);
}
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"))
{
"code": 200,
"data": [
{
"status": "submitted",
"task_id": "task_01K8SGYNNNVBQTXNR4MM964S7K"
}
]
}
{
"error": {
"code": 400,
"message": "请求参数无效",
"type": "invalid_request_error"
}
}
{
"error": {
"code": 401,
"message": "身份验证失败,请检查您的API密钥",
"type": "authentication_error"
}
}
{
"error": {
"code": 402,
"message": "账户余额不足,请充值后再试",
"type": "payment_required"
}
}
{
"error": {
"code": 403,
"message": "访问被禁止,您没有权限访问此资源",
"type": "permission_error"
}
}
{
"error": {
"code": 429,
"message": "请求过于频繁,请稍后再试",
"type": "rate_limit_error"
}
}
{
"error": {
"code": 500,
"message": "服务器内部错误,请稍后重试",
"type": "server_error"
}
}
{
"error": {
"code": 502,
"message": "网关错误,服务器暂时不可用",
"type": "bad_gateway"
}
}
Nano banana2
Nano Banana Lite Bildgenerierung
- Das schnellste und günstigste Bildmodell der Gemini-3.1-Reihe, ausgelegt auf skalierbare, kostengünstige Bildausgabe
- Unterstützt nur 1K-Auflösung (bei Übergabe von 2K/4K/0.5K erfolgt automatisch eine Herabstufung auf 1K, ohne Fehler)
- Unterstützt Text-zu-Bild und Bild-zu-Bild, bis zu 14 Referenzbilder
- Abrechnung nach Input-/Output-Token; direkte Anbindung an den offiziellen Gemini-Kanal, asynchrone Aufgabenausgabe
POST
/
v1
/
images
/
generations
# model kann "gemini-3.1-flash-lite-image" sein, ebenso kompatibel mit dem Alias "nano-banana-2-lite"
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
}'
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())
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));
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))
}
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
$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;
?>
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
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()
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);
}
}
#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;
}
#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;
}
(* 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
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);
}
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"))
{
"code": 200,
"data": [
{
"status": "submitted",
"task_id": "task_01K8SGYNNNVBQTXNR4MM964S7K"
}
]
}
{
"error": {
"code": 400,
"message": "请求参数无效",
"type": "invalid_request_error"
}
}
{
"error": {
"code": 401,
"message": "身份验证失败,请检查您的API密钥",
"type": "authentication_error"
}
}
{
"error": {
"code": 402,
"message": "账户余额不足,请充值后再试",
"type": "payment_required"
}
}
{
"error": {
"code": 403,
"message": "访问被禁止,您没有权限访问此资源",
"type": "permission_error"
}
}
{
"error": {
"code": 429,
"message": "请求过于频繁,请稍后再试",
"type": "rate_limit_error"
}
}
{
"error": {
"code": 500,
"message": "服务器内部错误,请稍后重试",
"type": "server_error"
}
}
{
"error": {
"code": 502,
"message": "网关错误,服务器暂时不可用",
"type": "bad_gateway"
}
}
Hinweis zur Modellnamen-Kompatibilität:
gemini-3.1-flash-lite-image ist mit dem Alias nano-banana-2-lite kompatibel, gemini-3.1-flash-lite-image-ext ist mit dem Alias nano-banana-2-lite-ext kompatibel. Jeder Name und sein Alias sind gleichwertig und austauschbar verwendbar.# model kann "gemini-3.1-flash-lite-image" sein, ebenso kompatibel mit dem Alias "nano-banana-2-lite"
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
}'
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())
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));
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))
}
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
$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;
?>
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
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()
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);
}
}
#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;
}
#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;
}
(* 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
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);
}
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"))
{
"code": 200,
"data": [
{
"status": "submitted",
"task_id": "task_01K8SGYNNNVBQTXNR4MM964S7K"
}
]
}
{
"error": {
"code": 400,
"message": "请求参数无效",
"type": "invalid_request_error"
}
}
{
"error": {
"code": 401,
"message": "身份验证失败,请检查您的API密钥",
"type": "authentication_error"
}
}
{
"error": {
"code": 402,
"message": "账户余额不足,请充值后再试",
"type": "payment_required"
}
}
{
"error": {
"code": 403,
"message": "访问被禁止,您没有权限访问此资源",
"type": "permission_error"
}
}
{
"error": {
"code": 429,
"message": "请求过于频繁,请稍后再试",
"type": "rate_limit_error"
}
}
{
"error": {
"code": 500,
"message": "服务器内部错误,请稍后重试",
"type": "server_error"
}
}
{
"error": {
"code": 502,
"message": "网关错误,服务器暂时不可用",
"type": "bad_gateway"
}
}
Autorisierung
string
erforderlich
Alle API-Endpunkte erfordern eine Authentifizierung per Bearer TokenAPI-Schlüssel erhalten:Besuchen Sie die Seite zur Verwaltung von API-Schlüsseln, um Ihren API-Schlüssel zu erhaltenFügen Sie ihn dem Anfrage-Header hinzu:
Authorization: Bearer YOUR_API_KEY
Body
string
Standard:"gemini-3.1-flash-lite-image"
erforderlich
Name des BildgenerierungsmodellsFolgende Modellnamen werden unterstützt:
gemini-3.1-flash-lite-image(Nano Banana Lite, kompatibler Aliasnano-banana-2-lite)gemini-3.1-flash-lite-image-ext(kompatibler Aliasnano-banana-2-lite-ext)
Beide haben identische Parameter und Einschränkungen (nur 1K, keine Unterstützung für
google_search / official_fallback, maximal 14 Referenzbilder). Für keinen der beiden gibt es eine -official-Variante, und der Fallback-Parameter official_fallback wird ebenfalls nicht unterstützt. Die Abrechnung richtet sich nach der Backend-Konfiguration des jeweiligen Kanals.Die Aliase nano-banana-2-lite (entspricht gemini-3.1-flash-lite-image) und nano-banana-2-lite-ext (entspricht gemini-3.1-flash-lite-image-ext) sind ihren jeweiligen Originalnamen gleichwertig und austauschbar verwendbar.string
erforderlich
Textbeschreibung für die Bildgenerierung
string
Seitenverhältnis des BildesUnterstützte Seitenverhältnisse:
auto– Seitenverhältnis automatisch wählen1:1– Quadrat, Avatare, soziale Medien3:2/2:3– Standardfotos4:3/3:4– Klassisches Bildschirmverhältnis16:9/9:16– Breitbild / Cover für vertikale Videos5:4/4:5– Bilder für Instagram21:9– Ultrabreites Banner
Bei Text-zu-Bild ist der Standardwert
1:1 oder 16:9, wenn size auf auto gesetzt ist; bei Bild-zu-Bild richtet sich das Seitenverhältnis nach der Antwort der vorgelagerten Quelle. (Wir empfehlen, ein Seitenverhältnis explizit anzugeben.)string
Standard:"1K"
Auflösung des AusgabebildesUnterstützte Werte:
1K– ~1024px, Standardauflösung (Lite unterstützt nur diese Stufe)
Lite unterstützt nur 1K. Bei Übergabe von
2K / 4K / 0.5K erfolgt eine stille Herabstufung auf 1K, ohne Fehler und ohne tatsächliche Ausgabe in hoher Auflösung. Die Frontend-UI muss keine Auflösungsoption anzeigen.integer
Standard:"1"
Anzahl der zu generierenden BilderWertebereich: 1 ~ 4, Standard
1Bei n>1 sendet das Backend mehrere gleichzeitige Anfragen an die vorgelagerte Quelle und rechnet nach der tatsächlichen Anzahl erfolgreich generierter Bilder ab. Wir empfehlen, im Frontend fest 1 zu übergeben (Fortschritt bildweise anzeigen, transparentere Abrechnung).⚠️ Hinweis: Es muss eine reine Zahl übergeben werden (z. B. 1), keine Anführungszeichen verwenden, sonst tritt ein Fehler aufarray
Liste der URLs von Referenzbildern für die Bild-zu-Bild-GenerierungEs werden zwei Formate unterstützt:1. Vollständige Bild-URL
- Öffentlich zugängliche Bild-URL (http:// oder https://)
- Beispiel:
https://example.com/image.jpg
- Es muss das vollständige Data-URI-Format verwendet werden
- Format:
data:image/{format};base64,{base64data} - Unterstützte Bildformate: jpeg, png, webp
- Beispiel:
data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAYABg... - ⚠️ Hinweis: Das Präfix
data:image/jpeg;base64,muss enthalten sein
- Maximal 14 Referenzbilder (empfohlen: bis zu 10 Objektreferenzen + 4 Charakterreferenzen)
- Größe eines einzelnen Bildes: maximal 10 MB
- Unterstützte Formate: jpeg, png, webp
string
Callback-Adresse der Aufgabe (base)Bei Erfolg / Fehlschlag der Aufgabe ruft diese Plattform
webhook + /callback auf (kein Weiterleiten an die vorgelagerte Quelle). Die Übergabe dieses Parameters kann das Polling deutlich reduzieren; wir empfehlen dennoch, das Polling als Absicherung beizubehalten.Wichtige Hinweise zur Nutzung von Lite
google_search/google_image_searchwerden nicht unterstützt: Lite verwendet deninteractions-Endpunkt der Developer API, die vorgelagerte Quelle stellt das Search-Tool nicht bereit (gibt “Search as tool is not enabled for this model” zurück), und der Plattform-Adapter sendet diesen Parameter nicht weiter. Bei Übergabe tritt kein Fehler auf, das Bild wird wie gewohnt generiert, jedoch ohne jegliche Sucherweiterung. Wenn Sie eine Sucherweiterung benötigen, verwenden Sie stattdessengemini-3.1-flash-image-preview.mask_urlfür lokales Inpainting wird nicht unterstützt (die Gemini-Reihe arbeitet mit aspect ratio + Referenzbildern, nicht mit Masken).- Abrechnung nach Token (im Unterschied zum festen Preis pro Bild bei flash/pro): Input ca. 0.25/MillionToken,Bildausgabeca.30/Million Token, ein 1K-Bild ≈ 1120 output token ≈ $0.0336/Bild. Der tatsächliche Preis richtet sich nach der Multiplikator-Konfiguration im Backend.
- Alle generierten Bilder enthalten Googles unsichtbares SynthID-Wasserzeichen (Verhalten der vorgelagerten Quelle, kann nicht deaktiviert werden).
Response
integer
Statuscode der Antwort
⌘I