Semantic Caching for LLM Apps: GPTCache vs Redis vs Upstash (2026)
A hands-on comparison of GPTCache, Redis LangCache, Upstash, and Canopy for semantic caching, with real hit rates, costs, and threshold-tuning lessons from production.
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A hands-on comparison of GPTCache, Redis LangCache, Upstash, and Canopy for semantic caching, with real hit rates, costs, and threshold-tuning lessons from production.
A production-tested comparison of vLLM, SGLang, TensorRT-LLM, and Ollama for self-hosted LLM serving in 2026 — throughput, cold-start, cost math, and decision matrix from running a 4-product AI backend on a shared H100.
A working engineer's view of the four libraries that actually solve the malformed-JSON problem in production AI: Instructor, BAML, Outlines, and Pydantic AI. Real benchmark numbers from 1.4M monthly LLM calls.
I ran the same LoRA fine-tune of Llama 3.1 8B on four platforms with 12,400 training pairs from our SmartExam product. Real costs, training times, inference latency, and the multi-adapter math that decided which one we shipped.
Gemma 4 review with real benchmarks. Apache 2.0 license, 89.2% AIME math, 34 tokens/sec on M2 MacBook. How it compares to Llama and what you can build with it.