7 techniques for building cost-efficient AI pipelines: routing, caching, batching
goyalshaliniuk · x · 2026-11-06
A practical framework for cost-efficient AI pipelines: route tasks to right-sized models, cache identical and semantically similar requests, keep prompts lean, batch independent requests via Batch APIs, optimize inference infra (quantization, right-sized hardware), run long tasks asynchronously with queues like Celery, and measure cost per successful task rather than total API spend. Recommended tools include LiteLLM (62.8k stars) as an AI gateway.
Related event: Seven Tricks to Cut AI Pipeline Costs Without Sacrificing Quality(2 posts)→
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