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Latest — 17 Mar 2026

Qwen 3 vs Llama 3 for Local Deployment: Which Model, What Hardware, and When to Skip DIY

Two years ago, running a useful LLM locally meant a $10,000 GPU and a lot of patience. Now a $400 RTX 3060 runs models that rival GPT-3.5. The question isn't whether you can run models locally. It's which model makes sense for your hardware,

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Multi-GPU LLM Inference: TP vs PP vs EP Parallelism Guide (2026)

Complete guide to multi-GPU LLM inference. Learn tensor parallelism, pipeline parallelism, expert parallelism with vLLM. Includes benchmarks, memory calculations, and decision framework.

Deploy Llama 4 with vLLM: Scout vs Maverick Setup Guide (2026)

Llama 4 looks impressive in Meta's announcement. 10 million token context on Scout. Maverick competing with GPT-4 on benchmarks. Native multimodal support. Efficient mixture-of-experts architecture. What the announcement didn't mention: Maverick needs 8× H100s minimum. The 10M context on Scout requires hardware most teams don'

RAG Chunking Strategies: The 2026 Benchmark Guide

Quick answer: Recursive character splitting at 512 tokens with 50 to 100 tokens of overlap is the benchmark-validated default for most RAG applications. It scored 69% accuracy in the largest real-document test of 2026, requires zero model calls, and outperformed every more expensive alternative. The rest of this guide covers

Hybrid Search for RAG: BM25, SPLADE, and Vector Search Combined

Quick answer: Hybrid search runs a sparse retriever (BM25 or SPLADE) and a dense vector retriever in parallel, then merges results with a fusion algorithm before passing chunks to the LLM. It consistently outperforms either method alone because dense retrieval misses exact identifiers and dense retrieval misses semantic matches. Start

Deploying LLMs on Kubernetes: vLLM, Ray Serve & GPU Scheduling Guide (2026)

Most K8s LLM guides stop at kubectl apply. This one covers GPU topology, KV-cache autoscaling, graceful shutdown, and canary deployments for production inference.

How to Self-Host DeepSeek R1: Hardware, Setup, and Privacy Guide (2026)

DeepSeek R1 is the first open-weight model that genuinely competes with OpenAI o1 on reasoning tasks. It scores 79.8% on AIME 2024, writes code at a Codeforces 2,029 Elo level, and ships under an MIT license. There's one problem. Every prompt you send to DeepSeek'

LLM Inference Servers Compared: vLLM vs TGI vs SGLang vs Triton (2026)

Compare vLLM, SGLang, TGI, and Triton for LLM inference. Real benchmarks, throughput data, and a decision matrix to pick the right server for your workload.

LLM Docker Deployment: Complete Production Guide (2026)

Getting an LLM running in a container takes maybe 20 minutes. Getting it to stay running under real traffic, survive restarts, and give your ops team something to monitor takes a lot longer. This guide covers the full path. Base image selection, CUDA setup, vLLM vs TGI tradeoffs, single and

How to Self-Host Mistral Large 3: Hardware, vLLM Setup & Function Calling (2026)

Self-host Mistral Large 3 on your own infrastructure. Hardware sizing, vLLM commands, function calling, Eagle speculative decoding, and production tips for the 675B MoE model.