Batch Processing Strategies
How to use the Anthropic Message Batches API for 50% cost savings on non-latency-sensitive workloads. Covers when to batch vs. when NOT to, custom_id correlation, failure handling, and the critical constraint that batch requests cannot do multi-turn tool calling.
Quick Reference
- →Message Batches API: 50% cost savings compared to synchronous API
- →Processing time: up to 24 hours, no guaranteed latency SLA
- →Appropriate for: overnight reports, weekly audits, nightly test generation, bulk extraction
- →NOT appropriate for: blocking pre-merge CI checks, real-time user-facing features
- →No multi-turn tool calling in batch requests -- each request is a single-turn exchange
- →Use custom_id to correlate request/response pairs across large batches
- →Handle partial failures: resubmit only failed requests, not the entire batch
- →Refine prompts on a sample set BEFORE batch-processing thousands of items
- →Batch API supports up to 100,000 requests per batch (check current limits)
- →Exam Scenario 5 (CI/CD): batch is WRONG for pre-merge checks but RIGHT for nightly audits
When to Use Batch vs. Synchronous API
The Message Batches API offers a simple tradeoff: you give up latency guarantees in exchange for 50% lower cost. The key question is whether your workflow can tolerate up to 24 hours of processing time.
| Characteristic | Synchronous API | Message Batches API |
|---|---|---|
| Cost | Standard pricing | 50% discount |
| Latency | Seconds (with SLA) | Up to 24 hours (no SLA) |
| Use case | Real-time, interactive, blocking | Background, overnight, non-blocking |
| Tool calling | Multi-turn supported | Single-turn only |
| Rate limits | Standard rate limits apply | Separate batch limits (higher throughput) |
| Result delivery | Immediate in response | Poll for completion or use webhook |
| Max requests | One at a time (parallel up to rate limit) | Up to 100,000 per batch |
| Error handling | Immediate retry | Resubmit failed items after batch completes |
The exam will present a scenario where a team uses the batch API for pre-merge code review in their CI/CD pipeline, and developers complain about slow merge times. The answer is ALWAYS: switch to synchronous API for pre-merge checks. Batch API has no latency SLA and should never be used for blocking workflows. However, batch IS appropriate for nightly/weekly audit runs of the same codebase.