# model pode ser "gemini-3.1-flash-lite-image", também compatível com o 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 Geração de imagens
- O modelo de imagens mais rápido e mais barato da família Gemini 3.1, focado em geração em escala e de baixo custo
- Suporta apenas resolução 1K (enviar 2K/4K/0.5K resulta em rebaixamento automático para 1K, sem erro)
- Suporta geração a partir de texto e a partir de imagem, com até 14 imagens de referência
- Cobrança por token de input / output; conexão direta ao canal oficial do Gemini, geração via tarefa assíncrona
POST
/
v1
/
images
/
generations
# model pode ser "gemini-3.1-flash-lite-image", também compatível com o 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"
}
}
Aviso de compatibilidade de nomes de modelo:
gemini-3.1-flash-lite-image é compatível com o alias nano-banana-2-lite, e gemini-3.1-flash-lite-image-ext é compatível com o alias nano-banana-2-lite-ext; cada nome é equivalente ao seu alias e pode ser usado de forma intercambiável.# model pode ser "gemini-3.1-flash-lite-image", também compatível com o 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"
}
}
Autorizações
string
obrigatório
Todos os endpoints da API requerem autenticação por Bearer TokenObtenha sua chave de API:Acesse a página de gerenciamento de chaves de API para obter sua chave de APIAdicione-a ao cabeçalho da requisição:
Authorization: Bearer YOUR_API_KEY
Body
string
padrão:"gemini-3.1-flash-lite-image"
obrigatório
Nome do modelo de geração de imagensOs seguintes nomes de modelo são suportados:
gemini-3.1-flash-lite-image(Nano Banana Lite, compatível com o aliasnano-banana-2-lite)gemini-3.1-flash-lite-image-ext(compatível com o aliasnano-banana-2-lite-ext)
Ambos têm os mesmos parâmetros e restrições (apenas 1K, não suporta
google_search / official_fallback, no máximo 14 imagens de referência). Nenhum deles possui variante -official, nem suporta o parâmetro de fallback official_fallback. A cobrança segue a configuração de backend do respectivo canal de cada um.Os aliases nano-banana-2-lite (correspondente a gemini-3.1-flash-lite-image) e nano-banana-2-lite-ext (correspondente a gemini-3.1-flash-lite-image-ext) são equivalentes aos seus respectivos nomes originais e podem ser usados de forma intercambiável.string
obrigatório
Descrição textual para a geração da imagem
string
Proporção da imagemProporções suportadas:
auto- Escolhe automaticamente a proporção1:1- Quadrado, avatares, redes sociais3:2/2:3- Fotos padrão4:3/3:4- Proporção tradicional de telas16:9/9:16- Widescreen / capas de vídeos verticais5:4/4:5- Imagens para Instagram21:9- Banner ultrawide
Para geração a partir de texto, quando
size é auto, o padrão é 1:1 ou 16:9; para geração a partir de imagem, a proporção segue a resposta do upstream. Recomendamos especificar uma proporção explicitamente.string
padrão:"1K"
Resolução da imagem de saídaValores suportados:
1K- ~1024px, resolução padrão (o Lite suporta apenas este nível)
O Lite suporta apenas 1K. Enviar
2K / 4K / 0.5K resulta em rebaixamento silencioso para 1K, sem gerar erro e sem produzir de fato uma resolução mais alta. A interface do frontend não precisa expor a opção de resolução.integer
padrão:"1"
Número de imagens a serem geradasIntervalo: 1 ~ 4, padrão
1Quando n>1, o backend faz várias requisições simultâneas ao upstream e cobra pelo número de imagens realmente geradas com sucesso. Recomendamos que o frontend envie sempre 1 (exibe o progresso imagem por imagem e torna a cobrança mais clara).⚠️ Observação: Deve ser um número puro (ex.: 1), não use aspas, caso contrário ocorrerá um erroarray
Lista de URLs de imagens de referência para geração a partir de imagemDois formatos são suportados:1. URL completo da imagem
- URL de imagem publicamente acessível (http:// ou https://)
- Exemplo:
https://example.com/image.jpg
- Deve usar o formato Data URI completo
- Formato:
data:image/{format};base64,{base64data} - Formatos de imagem suportados: jpeg, png, webp
- Exemplo:
data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAYABg... - ⚠️ Observação: É necessário incluir o prefixo
data:image/jpeg;base64,
- Máximo de 14 imagens de referência (recomendado: até 10 referências de objetos + 4 referências de personagens)
- Tamanho de uma única imagem: não exceder 10 MB
- Formatos suportados: jpeg, png, webp
string
Endereço de callback da tarefa (base)Quando a tarefa é concluída com sucesso / falha, a plataforma faz o callback para
webhook + /callback (não encaminha o upstream). Enviar este parâmetro reduz significativamente o polling; ainda assim, recomendamos manter o polling como mecanismo de reserva.Pontos importantes de uso do Lite
- Não suporta
google_search/google_image_search: o Lite usa o endpointinteractionsda Developer API, e o upstream não disponibiliza a ferramenta de Search (retorna “Search as tool is not enabled for this model”), e o adaptador da plataforma também não envia esse parâmetro. Enviá-lo não gera erro e a imagem é gerada normalmente, mas sem qualquer efeito de aprimoramento por busca. Se precisar de aprimoramento por busca, usegemini-3.1-flash-image-preview. - Não suporta repintura local via
mask_url(a família Gemini usa aspect ratio + imagens de referência, não máscaras). - Cobrança por token (diferente do preço fixo por imagem do flash/pro): entrada de cerca de 0.25/milha~odetokens,saıˊdadeimagemdecercade30/milhão de tokens, uma única imagem 1K ≈ 1120 tokens de output ≈ $0.0336/imagem. O preço real segue a configuração de multiplicador do backend.
- Todas as imagens geradas contêm a marca d’água invisível SynthID do Google (comportamento do upstream, não pode ser desativado).
Response
integer
Código de status da resposta
⌘I