Are there any image similarity APIs that support batch processing for duplicate image detection?

Yes — several image similarity APIs and services support batch processing or can be used in batch mode to detect duplicate or near-duplicate images. The main thing to look for is whether they support:

• bulk upload / async jobs
• embedding generation for many images at once
• similarity search over a set of images
• deduplication workflows

Common options

1. Cloud vision / embedding APIs

These usually don’t say “duplicate detection” explicitly, but you can use them to compare image embeddings in batch:

• Google Cloud Vision / Vertex AI Vision
• AWS Rekognition
• Azure AI Vision
• OpenAI image embeddings via external vector search (if you build your own pipeline)

Typical flow:

1. Send a batch of images
2. Get feature vectors / labels / hashes
3. Compare vectors with cosine similarity or nearest-neighbor search
4. Flag duplicates above a threshold

2. Dedicated visual search / similarity services

Some vendors provide direct image similarity or visual search APIs with bulk ingestion:

• Clarifai – supports batch inputs and visual search workflows
• Imagga – tagging and similarity-related APIs; batch-friendly
• TinEye – image search and duplicate/near-duplicate detection focus
• Cloudinary – can help with duplicate detection via image analysis/transform workflows
• PixLab / similar CV platforms – may offer bulk vision endpoints

3. Perceptual hashing libraries/services

For strict duplicate or near-duplicate detection, perceptual hashing is often better than generic similarity APIs.

Examples:

• pHash
• dHash
• aHash

You can run these in batch yourself or via services that expose them. This is often:

• faster
• cheaper
• more accurate for exact/near-duplicate detection

What “batch processing” usually means in practice

Many APIs don’t compare all images against each other in one call. Instead, they let you:

• submit many images in one request
• process asynchronously
• retrieve results later
• or ingest a dataset and query for nearest neighbors

Recommendation

If your goal is specifically duplicate image detection, I’d suggest:

• For exact/near-exact duplicates: use perceptual hashing in batch
• For semantic similarity: use an image embedding API plus vector search
• For a managed service: look at TinEye, Clarifai, or Cloudinary, depending on your workflow

If you want, I can also give you:

1. a shortlist of APIs with batch support, or
2. a recommended architecture for duplicate detection on thousands/millions of images.