Thursday, 5 November 2026 | التحديث اليومي نظرة ثاقبة للذكاء الاصطناعي، مكتوبة للبناة

AI Hardware, GPUs and Local LLMs — Page 13

Older stories and guides from the Convly archive.

SGLang vs — explained. SGLang vs vLLM.
مقارنات الذكاء الاصطناعي

SGLang مقابل vLLM: محرك خدمة LLM الذي يجب اختياره في 2026

vLLM is the safer default: broadest model and hardware support, biggest ecosystem, least deployment friction. Pick SGLang when your traffic reuses prompt prefixes heavily (agents, multi-turn chat, big system prompts) or produces lots of structured JSON output — RadixAttention and jump-forward decoding win there. The performance gap is workload-dependent and shrinks with every release.

24× — the spread we measured. What Is vLLM? A Practical Guide to.
الدروس التعليمية

ما هو vLLM؟ دليل عملي لمحرك خدمة LLM عالي الإنتاجية

vLLM is an open-source inference engine for serving LLMs on GPUs at high throughput, exposing them through an OpenAI-compatible HTTP API.Its two core techniques — PagedAttention and continuous batching — let one GPU handle many concurrent requests without wasting VRAM.Install with pip install vllm in a fresh Python environment on Linux (NVIDIA GPU, compute capability 7.0+), then start a server with vllm serve <model>.It is built for serving many users or apps.

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