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SimHash Fingerprint & Near-Duplicate Detection
x402
SimHash Fingerprint & Near-Duplicate Detection is a paid API for AI agents from api.24klabs.ai, paid per call via x402, $0.002/call, status unknown (last checked 2026-09-13).
Computes a 64-bit SimHash fingerprint for text content, or compares two texts returning Hamming distance and a 0–1 similarity score for near-duplicate detection.
Price / call$0.002
Success—
StatusUnknown
How this service works
Compute a 64-bit SimHash fingerprint for content, or compare two texts and return the Hamming distance and a 0-1 similarity score for near-duplicate detection.
Output
For a single text input: a 64-bit SimHash fingerprint (integer or hex string). For a two-text comparison: the Hamming distance (integer, 0–64) between the two fingerprints and a normalized 0–1 similarity score where values near 1 indicate near-duplicates.
Example use cases
News article deduplication pipeline
“I have two scraped news articles and I want to know if they're near-duplicates — can you run a SimHash comparison on them and give me the Hamming distance and similarity score?”
Blog post plagiarism check
“Compare these two blog posts using SimHash and tell me how similar they are on a 0-to-1 scale and the Hamming distance between their fingerprints.”
Content fingerprinting for a crawl cache
“Generate a 64-bit SimHash fingerprint for this webpage text so I can store it and later detect if the page has changed significantly.”
Technical details
Endpoint
POSThttps://api.24klabs.ai/api/simhash-dedupWhen to prefer
Choose this endpoint when you need fast, deterministic near-duplicate detection for text without requiring semantic understanding — ideal for deduplication of crawled web pages, news feeds, user-generated content, or document archives. Prefer it over cosine similarity or embedding-based approaches when speed and exact fingerprint reproducibility matter more than semantic nuance, and when you want a single cheap hash you can store and compare later.
Side effects
- Empty or missing text input returns a 400 validation error
- Extremely short texts (1–2 words) may produce unreliable similarity scores
- Non-textual binary content causes parsing errors
- Rate limiting or payment failure results in 402/429 responses
- Very large text inputs may be truncated or rejected with a payload-size error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| a | string | |
| b | string |
Output
Schema · Response
{
"type": "json",
"example": {
"distance": 3,
"similarity": 0.95
}
}Tags
x402
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