Tag: #tensorrt-llm
Writing on GPUs, LLMs, MLOps, Kubernetes — and mindset · 8 posts
LLM Inference Serving 2026 — Comparing vLLM, SGLang, and TensorRT-LLM
A clear overview of LLM inference serving in 2026. From core principles such as the difference in nature between prefill and decode, continuous batching, and paged KV cache, to a strengths-and-weaknesses comparison of vL
2026-06-26 · 15 min read #llm-serving#vllm#sglang#tensorrt-llm#inferenceLLM Serving & Local Inference in 2026 — vLLM / llama.cpp / MLX / Ollama / LM Studio / SGLang / TGI Deep Dive
A map of the 2026 LLM serving and inference landscape. Datacenter camp (vLLM, SGLang, TGI, Triton, TensorRT-LLM), local camp (llama.cpp, MLX, llamafile, Ollama, LM Studio, GPT4All), emerging camp (KTransformers, MLC LLM,
2026-05-16 · 25 min read #llm#model-serving#inference#vllm#llama-cppAI Inference Engines 2026 - vLLM · SGLang · llama.cpp · TGI · TensorRT-LLM · MLX · mistral.rs · DeepSpeed-MII · Aphrodite Deep Dive
In 2026, LLM engineering is no longer about which model — it is about which inference engine. We dissect vLLM V1, SGLang 0.4, TensorRT-LLM, TGI 3.x, llama.cpp, MLX-LM, mistral.rs, DeepSpeed-MII, Aphrodite, CTranslate2, E
2026-05-16 · 20 min read #llm-inference#vllm#sglang#llama-cpp#tgiComplete LLM Inference Optimization Guide 2025: vLLM, TensorRT-LLM, KV Cache, Speculative Decoding
Everything about LLM inference optimization! vLLM (PagedAttention), TensorRT-LLM (FP8/INT4), KV Cache management, Speculative Decoding, Continuous Batching, FlashAttention, Quantization (GPTQ/AWQ/GGUF), Model Serving (Tr
2026-04-14 · 25 min read #llm-inference#vllm#tensorrt-llm#kv-cache#speculative-decodingGPU Memory Management & LLM Inference Optimization: vLLM, PagedAttention, GPTQ, TensorRT-LLM
A complete guide to LLM inference optimization covering HBM memory hierarchy, KV cache calculations, PagedAttention, GPTQ/AWQ quantization, continuous batching, and vLLM vs TensorRT-LLM comparison.
2026-03-17 · 16 min read #gpumemory#llminference#vllm#paged-attention#gptqThe Complete Guide to LLM Inference Optimization: vLLM, TensorRT-LLM, Speculative Decoding
A comparative analysis of key technologies for maximizing LLM inference performance — vLLM, TensorRT-LLM, Speculative Decoding, and KV Cache optimization — with practical code examples and benchmarks.
2026-03-14 · 19 min read #llm#inference-optimization#vllm#tensorrt-llm#speculative-decodingLLM Inference Serving Framework Comparison: TensorRT-LLM vs vLLM vs SGLang Production Deployment Strategy
A comparison of LLM inference serving frameworks — TensorRT-LLM, vLLM, and SGLang — with production deployment strategies.
2026-03-12 · 21 min read #llm#inference#tensorrt-llm#vllm#sglangLLM Inference Optimization: In-Depth Analysis of vLLM and TensorRT-LLM
Analyzing core LLM inference optimization techniques including PagedAttention, Continuous Batching, and quantization, based on the official documentation of vLLM and TensorRT-LLM.
2026-03-01 · 22 min read #llm#inference#vllm#tensorrt-llm#optimization