Process 10K Tasks at 50% Cost with Claude Batch API

The Claude Message Batches API is designed for professional workloads that don't require real-time responses-think document classification, content analysis, data extraction, or bulk research synthesis. Instead of sending individual requests at standard API pricing, you package up to 100,000 queries into a single batch submission, and Claude processes them asynchronously at exactly 50% of per-token costs.

Here's how to implement it: Use the Anthropic Python SDK to create a batch with a list of message requests, each tagged with a custom_id. Each request follows the standard Messages API format-model, max_tokens, system prompt, and messages. Once submitted via client.beta.messages.batches.create(), the API assigns a batch ID and begins processing. Results are typically available within an hour (though the platform guarantees completion within 24 hours), and you can poll status with client.beta.messages.batches.retrieve(batch_id). Results persist for 29 days.

Practical example: A compliance team needs to classify 5,000 vendor contracts by risk category. Using standard API calls would cost $500; the same batch costs $250. Set up requests with instructions like "Classify this contract as HIGH, MEDIUM, or LOW risk based on payment terms, liability clauses, and termination conditions," attach each contract as a custom_id, submit the batch, and retrieve results overnight. No real-time waiting, no token bleed.

The key constraint: streaming and fast mode are unsupported in batches, so this works best for tasks where you already have a collection of inputs and can tolerate asynchronous processing. Combine batch processing with Claude's prompt caching for even deeper savings on repeated context-enterprises report stacking both techniques to achieve 75% cost reductions on large-scale operations.