LangChain vs LlamaIndex (2026): Complete Production RAG Comparison
LangChain vs LlamaIndex 2026. RAG pipelines, agent frameworks, LangSmith vs Langfuse, breaking changes, and a no-BS decision guide for production teams.
Arnav Jalan
Building a Production LLM API Server: FastAPI + vLLM Complete Guide (2026)
Complete guide to production LLM APIs: FastAPI wrapper for vLLM with authentication, token-aware rate limiting, SSE streaming, and observability.
Building Production RAG: Architecture, Chunking, Evaluation & Monitoring (2026 Guide)
Build production RAG that actually works at scale. Covers chunking strategies with benchmarks, embedding selection, hybrid retrieval, reranking, RAGAS evaluation, latency budgets, and monitoring.
RAG Evaluation: Metrics, Frameworks & Testing (2026)
The complete guide to RAG evaluation metrics. Faithfulness, context precision, recall, LLM-as-judge. Code for Ragas and DeepEval. CI/CD integration included.
GraphRAG Implementation Guide: Entity Extraction, Query Routing & When It Beats Vector RAG (2026)
Build GraphRAG systems that connect the dots vector search misses. Covers Microsoft approach, LlamaIndex patterns, indexing costs, and when graph retrieval beats embeddings.
Speculative Decoding: 2-3x Faster LLM Inference (2026)
How speculative decoding works, draft model selection, EAGLE3 vs Medusa, acceptance rate math, vLLM and SGLang setup. Real benchmarks from Llama 3.1 on H100s.
Best Embedding Models for RAG (2026): Ranked by MTEB Score, Cost, and Self-Hosting
10 best embedding models for RAG in 2026 with MTEB benchmarks, cost per million tokens, max context length, dimensions, and a decision guide for your use case.
LLM Quantization Guide: GGUF vs AWQ vs GPTQ vs bitsandbytes Compared (2026)
A 70B parameter model in FP16 takes 140GB of memory. Most people don't have that kind of hardware.
Quantization solves this by compressing weights from 16-bit floats to 4-bit integers, shrinking models by 75% with surprisingly little quality loss. A Llama 3 70B that normally requires multiple A100s
KV Cache Optimization: PagedAttention, Prefix Caching & Memory Management
KV cache optimization guide covering PagedAttention, prefix caching, FP8 quantization, and memory management. Practical strategies for production LLM inference.
LLM Latency Optimization: From 5s to 500ms (2026)
Why your LLM is slow and how to fix it. TTFT reduction, quantization benchmarks, prefix caching, model selection, hardware sizing. From 5s to 500ms in practice.