The industry's most advanced, multi-task AI solver for Tencent Slider (滑动拼图), Sequence Order Click (顺序点击), and Spatial Category captchas. Sub-200ms latency at an unbeatable price of $0.99 / 1000 solves.
One unified API endpoint to automate all variations of Tencent TCaptcha, WeChat, QQ, and Chinese character challenges.
Captchas with an instruction strip displaying 3 specific icons to click in order on the background canvas. Our pure AI pipeline matches icons via Siamese Deep Metric cosine embeddings.
Detects the exact horizontal target coordinate (center_x) for sliding puzzle pieces with sub-pixel precision. Fully handles shadow gaps, textured backgrounds, and distorted pieces.
Classifies and locates objects belonging to a target semantic category (e.g. clocks, lamps, umbrellas) across 6-grid or free-form canvas areas with multi-target coordinate returns.
Plug into your existing Python, Node.js, PHP, or cURL bots in less than 5 minutes.
import requests
import base64
API_KEY = "ck_your_api_key_here"
# 1. Read Target Instruction Strip & Background images
with open("target_strip.png", "rb") as ft, open("background.png", "rb") as fb:
target_b64 = base64.b64encode(ft.read()).decode("utf-8")
bg_b64 = base64.b64encode(fb.read()).decode("utf-8")
# 2. Call CaptchaKings API
response = requests.post(
"https://captchakings.com/api/tencent.php",
headers={
"Authorization": f"Bearer {API_KEY}",
"Content-Type": "application/json"
},
json={
"type": "sequence",
"target_image_base64": target_b64,
"bg_image_base64": bg_b64
},
timeout=30
)
data = response.json()
if data.get("success"):
print("Ordered Click Coordinates:", data["click_coordinates"])
# Example Output: [[439, 357], [600, 437], [360, 117]]
print("Latency:", data["processing_time"])
else:
print("Error:", data.get("error"))
import requests
import base64
API_KEY = "ck_your_api_key_here"
with open("slider_bg.png", "rb") as f:
bg_b64 = base64.b64encode(f.read()).decode("utf-8")
response = requests.post(
"https://captchakings.com/api/tencent.php",
headers={"Authorization": f"Bearer {API_KEY}"},
json={
"type": "slider",
"image_base64": bg_b64
}
)
data = response.json()
if data.get("success"):
print("Target Slider X:", data["slider_position"]["center_x"])
print("Confidence:", data["confidence"])
const fs = require('fs');
async function solveTencentCaptcha() {
const targetB64 = fs.readFileSync('target_strip.png').toString('base64');
const bgB64 = fs.readFileSync('background.png').toString('base64');
const res = await fetch('https://captchakings.com/api/tencent.php', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'Authorization': 'Bearer ck_your_api_key_here'
},
body: JSON.stringify({
type: 'sequence',
target_image_base64: targetB64,
bg_image_base64: bgB64
})
});
const result = await res.json();
if (result.success) {
console.log('Click coordinates in order:', result.click_coordinates);
}
}
solveTencentCaptcha();
curl -X POST https://captchakings.com/api/tencent.php \
-H "Authorization: Bearer ck_your_api_key_here" \
-H "Content-Type: application/json" \
-d '{
"type": "sequence",
"target_image_base64": "iVBORw0KGgoAAAANSUhEUgAA...",
"bg_image_base64": "iVBORw0KGgoAAAANSUhEUgAA..."
}'
<?php
$apiKey = "ck_your_api_key_here";
$payload = [
'type' => 'sequence',
'target_image_base64' => base64_encode(file_get_contents('target_strip.png')),
'bg_image_base64' => base64_encode(file_get_contents('background.png'))
];
$ch = curl_init('https://captchakings.com/api/tencent.php');
curl_setopt_array($ch, [
CURLOPT_POST => true,
CURLOPT_POSTFIELDS => json_encode($payload),
CURLOPT_RETURNTRANSFER => true,
CURLOPT_HTTPHEADER => [
'Content-Type: application/json',
'Authorization: Bearer ' . $apiKey
]
]);
$response = curl_exec($ch);
curl_close($ch);
$data = json_decode($response, true);
if ($data['success']) {
print_r($data['click_coordinates']);
}
?>
How our client solver injects into the Tencent iframe and automatically simulates natural mouse clicks on the canvas.
// Injected Browser Automation Script (Handles scaling & natural click events)
async function solveTencentIframe(iframeDoc, apiKey) {
const bgEl = iframeDoc.querySelector('#slideBg, .tc-bg-img');
const targetEl = iframeDoc.querySelector('.tc-instruction-icon img, #instructionIcon img, .tc-desc-img img');
if (!bgEl || !targetEl) return false;
// Helper: Convert DOM image to base64
const toBase64 = (img) => {
const c = document.createElement('canvas');
c.width = img.naturalWidth || img.width;
c.height = img.naturalHeight || img.height;
c.getContext('2d').drawImage(img, 0, 0);
return c.toDataURL('image/png').split(',')[1];
};
// Call CaptchaKings API
const res = await fetch('https://captchakings.com/api/tencent.php', {
method: 'POST',
headers: { 'Content-Type': 'application/json', 'Authorization': 'Bearer ' + apiKey },
body: JSON.stringify({
type: 'sequence',
target_image_base64: toBase64(targetEl),
bg_image_base64: toBase64(bgEl)
})
});
const data = await res.json();
if (!data.success) throw new Error(data.error);
// Calculate natural canvas coordinate scaling
const bgRect = bgEl.getBoundingClientRect();
const scaleX = bgRect.width / (bgEl.naturalWidth || 680);
const scaleY = bgRect.height / (bgEl.naturalHeight || 480);
// Dispatch Ordered Mouse Clicks
for (const [x, y] of data.click_coordinates) {
const clickX = bgRect.left + (x * scaleX);
const clickY = bgRect.top + (y * scaleY);
bgEl.dispatchEvent(new MouseEvent('mousedown', { bubbles: true, clientX: clickX, clientY: clickY, button: 0, buttons: 1 }));
await new Promise(r => setTimeout(r, 60));
bgEl.dispatchEvent(new MouseEvent('mouseup', { bubbles: true, clientX: clickX, clientY: clickY, button: 0, buttons: 0 }));
bgEl.dispatchEvent(new MouseEvent('click', { bubbles: true, clientX: clickX, clientY: clickY, button: 0 }));
await new Promise(r => setTimeout(r, 300));
}
// Trigger Verification Submit
const verifyBtn = iframeDoc.querySelector('#verifyBtn, .tc-verify-button, .tc-verify-button-wrap button');
if (verifyBtn) verifyBtn.click();
return true;
}
Compare our Tencent Captcha solving performance, speed, and pricing against competitors.
| Feature / Metric | CaptchaKings | 2Captcha | CapSolver | Anti-Captcha |
|---|---|---|---|---|
| Price per 1,000 Solves | $0.99 - $1.00 | $2.99 | $1.80 | $2.00 |
| Average Solving Speed | < 0.20s (170ms) | 15 - 30s (Human) | 1.5 - 3.0s | 10 - 25s |
| Verified Accuracy | 97.0% | 78 - 85% | 90 - 92% | 80 - 88% |
| Sequence Order Click Support | Yes (Pure AI) | Slow Human | Yes | Partial |
| Slider Puzzle (V1 & V2) | Yes (Sub-pixel) | Yes | Yes | Yes |
| Free Starting Balance | $0.50 Instant | $0.00 | $0.00 | $0.00 |
Everything you need to know about our Tencent and Chinese Captcha solving technology.
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