Articles tagged “LLM”
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6 min readModel Quantization in 2026: 4-bit, 8-bit, and the Tradeoffs
A 2026 guide to model quantization — GPTQ, AWQ, GGUF, FP8, and INT8 — with quality-vs-speed tradeoffs, hardware support, and a practical serving recipe.
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6 min readSelf-Hosting LLMs in 2026: When It Pays Off
The honest 2026 math on self-hosting LLMs — break-even volumes, hidden engineering costs, model picks, and when regulatory drivers override the cost question.
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5 min readPrompt Caching Explained: Anthropic, OpenAI, and the Math
How prompt caching works at Anthropic and OpenAI in 2026 — cache breakpoints, write and read pricing, TTL, breakeven math, and how to design cache-friendly prompts.
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5 min readvLLM vs TGI vs SGLang: Inference Engines Compared
A 2026 comparison of vLLM, TGI, and SGLang inference engines — PagedAttention, RadixAttention, throughput, and which engine fits which production workload.
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5 min readThe Agentic AI Stack: From Tool Use to Autonomous Workflows
How the AI agent stack is layered in 2026 — model, framework, tools, memory, observability, evaluation — and the design decisions that matter at each layer.
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6 min readFine-Tuning vs RAG: The 2026 Decision Framework
A 2026 framework for choosing between fine-tuning and RAG — what each does, when each wins, and the hybrid pattern that most production systems actually use.
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6 min readAI Inference Cost Optimization: Practical Wins
Concrete tactics to cut LLM inference cost in 2026 — prompt caching, model cascading, batching, smaller models, and observability. With the math and a worked example.
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6 min readRAG Best Practices in 2026: Chunking, Reranking, Hybrid Search
The 2026 RAG playbook — chunking strategies, hybrid retrieval, rerankers, and how long context fits in. Practical defaults and the four levers that move quality.
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5 min readGPT-5.5 vs Claude 4: A Head-to-Head Comparison in 2026
A practical comparison of GPT-5.5 and Claude 4 in 2026 — coding, reasoning, context, safety, pricing, and when to choose each.
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4 min readLLM Jailbreak Prevention: A Practical Guide for 2026
How to defend production LLM applications against jailbreak attacks in 2026 — layered defenses, red teaming, and trade-offs.
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