Free 2026 guide maps LLM inference engines to hardware, from laptops to GPU clusters
blaizedsouza · x · 2026-09-07
Ahmad Osman's article "Inference Engines for LLMs & Local AI Hardware (2026 Edition)" — dubbed the bible for running LLMs locally — is now free to read online.
His core framing: don't pick an inference engine first; pick a hardware strategy, a workload shape, and a serving model, and the engine follows.
Coverage includes:
- Hardware scenarios: laptop/edge/odd hardware, Mac-first workflows, single RTX GPUs, 2-4+ NVIDIA/CUDA GPUs, production serving, long-context/MoE/routing, NVIDIA max performance, cluster orchestration
- Software: llama.cpp, MLX/MLX-LM, ExLlamaV2/V3, vLLM, SGLang, TensorRT-LLM, NVIDIA Dynamo
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