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 median latency at $1.00 / 1000 solves.
Chinese & Tencent Captcha Solver automates all 3 Tencent TCaptcha challenges (sequence order click, icon click, and slider) via high-speed API. CaptchaKings solves Chinese captchas with 97.0% accuracy and ~170ms median response time at $1.00 per 1,000 solves ($0.001/solve). Free trial includes a $0.50 balance for instant API testing.
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 | $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.
• Coordinates are returned in natural image pixels — scale them if the captcha iframe renders the image at a different CSS size.
• Order-click challenges: click the icons in the exact returned sequence — order mistakes count as failures.
• Slider: replay a human-like 600–900ms drag trajectory; instant jumps may fail behavioral checks.
Use this solver only on systems you own or are explicitly authorized to test (QA automation, accessibility tooling, research, load testing). You are responsible for complying with each target site's Terms of Service and applicable law. Details: Terms of Service.
Last verified: August 30, 2026 — accuracy and speed figures from /benchmarks (500+ production samples).
Start solving Chinese captchas today with 97% measured accuracy and ~170ms median latency — methodology at /benchmarks.
Claim $0.50 Free Balance