Process Bulk Data with Claude Batch API at 50% Discount

Claude's Batch API processes up to 10,000 requests asynchronously in under 24 hours for exactly half the normal cost. Perfect for analyzing large datasets, classifying support tickets, or processing document repositories where real-time responses aren't critical-turning expensive one-by-one API calls into economical bulk operations.

The Batch API is purpose-built for non-time-sensitive workloads where cost matters more than latency. Instead of making individual API calls that hit you per-request, you submit a batch file containing up to 10,000 requests, and Claude processes them all asynchronously and returns results in bulk-at 50% of standard pricing for both input and output tokens. A single batch takes less than 24 hours to complete, making it ideal for overnight processing pipelines.

The practical application: imagine a customer success team needs to analyze 2,000 support tickets to identify common complaint categories, suggest responses, and tag priority levels. Running each ticket through the API individually at standard rates would cost $500. The same 2,000 tickets processed as a single batch costs $250. You submit the batch at 5 PM, get results by 9 AM the next day, and your results are ready for team review at standup. For teams processing documents at scale-analyzing quarterly reports, extracting data from contracts, or reviewing code repositories-the Batch API makes analysis economically viable.

The workflow is straightforward: format your requests as a JSONL file (one request per line), call the batches endpoint with your file, get back a batch ID, and poll for completion. The API handles retries automatically, including throttled requests, so you don't need to manage manual retries. The output is returned in the same order as your input, making it easy to map results back to your source data.

Claude's batch processing currently supports Claude Opus 5, Claude Opus 4.8, Claude Opus 4.7, Claude Sonnet, and Haiku models on the Anthropic API. Customers using Claude through Amazon Bedrock can already use batch inference, and Google Cloud Vertex AI support is in preview. For teams running pipelines regularly, the math compounds: processing 50,000 documents per month at a 50% discount adds up to thousands of dollars saved, making what was previously uneconomical now standard practice.