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LLM Inference Engineering Handbook: Crush API Costs, Cut Latency and Build Reliable Production Systems Real Benchmarks, Python Code and Complete Code Repository for Engineers at Scale
LLM Inference Engineering Handbook: Crush API Costs, Cut Latency and Build Reliable Production Systems Real Benchmarks, Python Code and Complete Code Repository for Engineers at Scale
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LLM Inference Engineering Handbook: Crush API Costs, Cut Latency and Build Reliable Production Systems Real Benchmarks, Python Code and Complete Code Repository for Engineers at Scale
LLM Inference Engineering Handbook: Crush API Costs, Cut Latency and Build Reliable Production Systems Real Benchmarks, Python Code and Complete Code Repository for Engineers at Scale
This book fixes that. Based on real benchmarks from production systems running 10,000+ queries per day, LLM Inference Engineering Handbook documents the exact techniques that reduce API costs by 73% and cut average response time by 57% — without touching quality.
LLM Inference Engineering Handbook: Crush API Costs, Cut Latency and Build Reliable Production Systems Real Benchmarks, Python Code and Complete Code Repository for Engineers at Scale
Item #: 247161438

LLM Inference Engineering Handbook: Crush API Costs, Cut Latency and Build Reliable Production Systems Real Benchmarks, Python Code and Complete Code

Item #: 247161438

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This book fixes that. Based on real benchmarks from production systems running 10,000+ queries per day, LLM Inference Engineering Handbook documents the exact techniques that reduce API costs by 73% and cut average response time by 57% — without touching quality.
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Shop LLM Inference Engineering Handbook: Crush API Costs, Cut Latency and Build Reliable Production Systems Real Benchmarks, Python Code and Complete Code Repository for Engineers at Scale online at a best price in Colombia. B0H4125RN7
  • Your LLM system works. Your API bill doesn't.You've built something that runs. Users are happy. But last month's invoice landed like a punch: thousands of dollars in API costs, response times that spike without warning, and a CFO asking questions you don't have clean answers to.You're not doing anything wrong. You're just running a system that was never optimized for production reality.This book fixes that.Based on real benchmarks from production systems running 10,000+ queries per day, LLM Inference Engineering Handbook documents the exact techniques that reduce API costs by 73% and cut average response time by 57% — without touching quality.Every number in this book was measured, not estimated.You'll build a complete optimization stack from scratch:Cost profiling — find exactly where your money goes before optimizing anythingPrompt compression — remove 30-40% of redundant tokens without losing semantic meaningMulti-layer caching — eliminate 40-70% of API calls with exact match and semantic cache combinedModel routing — send simple queries to fast, cheap models and complex queries to powerful ones, automaticallyAsync and batching — increase throughput 4x without changing your logicLatency engineering — understand TTFT, p99, and why your worst 10% of users define your product's reputationRAG cost optimization — stop sending 5,000 tokens of context when 800 will doReliability patterns — retry loops, circuit breakers, and fallback chains that prevent the $4,000 outage billObservability stack — monitor cost, latency, and quality drift before users noticeProduction playbooks — step-by-step response guides for cost spikes, latency degradation, and quality regressionEvery chapter ships with production-ready Python code and a complete implementation in the companion code repository. Not pseudocode. Not simplified examples. Code you can run today.This is not a book about what LLMs are. It's a book for engineers who already know — and need systems that work at scale without burning budget.If your LLM system is in production and the economics aren't working yet, this is the book that changes that.The first technique in Chapter 1 takes 20 minutes to implement. Most engineers see measurable results the same day.
Publisher Independently published
Publication date June 2, 2026
Language English
Print length 201 pages
ISBN-13 979-8199736466
Item Weight 1.32 pounds (600 grams)
Dimensions 8.5 x 0.46 x 11 inches (21.6 x 1.2 x 27.9 cm)

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LLM Inference Engineering Handbook: Crush API Costs, Cut Latency and Build Reliable Production Systems Real Benchmarks, Python Code and Complete Code Repository for Engineers at Scale

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Features & Benefits

  • Reduce API costs by 73% with proven techniques.
  • Cut average response time by 57% while maintaining quality.
  • Includes production-ready Python code for immediate implementation.
  • Features real benchmarks from high-query production systems.
  • Comprehensive step-by-step playbooks for cost management.
  • Perfect for engineers seeking optimized production systems.

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