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Deploy Zhipu AI's GLM-4.5-Air LLM with SGLang on Dedicated GPU Servers

By PulseAugur Editorial · [1 sources] ·

This guide details how to deploy the GLM-4.5-Air-FP8 large language model on a dedicated NVIDIA GPU server using the SGLang framework. The process involves setting up an Ubuntu environment, installing SGLang, and configuring the model to expose an OpenAI-compatible API. The GLM-4.5-Air model, developed by Zhipu AI, is an expert model designed for reasoning and coding tasks, featuring approximately 106 billion total parameters with 12 billion active during inference. AI

IMPACT Enables self-hosting of advanced LLMs for greater control over inference and API access.

RANK_REASON Guide on deploying an existing LLM using specific software and hardware.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Deploy Zhipu AI's GLM-4.5-Air LLM with SGLang on Dedicated GPU Servers

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59 / 100
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Guide on deploying an existing LLM using specific software and hardware.
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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infra, model release
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Thea Lauren ·

    How to Deploy GLM-4.5-Air with SGLang on a Dedicated GPU Server

    <p>Running a large language model on dedicated hardware gives you full control over the serving environment, model configuration and API access. In this guide, we deploy <strong>GLM-4.5-Air-FP8</strong> from Z.ai on an NVIDIA GPU server using <strong>SGLang</strong>, exposing an …

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