2026 最佳AI 模型部署工具

探索 AI 模型部署工具與平台,協助將機器學習模型上線、擴展、監控並管理生產環境中的推論服務。

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AI 基礎設施

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產品

SGLang preview
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SGLang

AI 推論平台

SGLang is an open-source serving framework for large language and multimodal models. It helps developers deploy model servers and query them through OpenAI-compatible endpoints across supported GPU, CPU, TPU, NPU, and XPU platforms.

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Microsoft Foundry preview
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Microsoft Foundry

AI 智能體基礎設施

Microsoft Foundry is an enterprise AI platform for building, grounding, deploying, and governing AI applications and agents. It helps development and data teams connect models, organizational knowledge, business tools, and lifecycle controls in Azure.

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Paperspace preview
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Paperspace

AI 模型部署

Paperspace is a cloud platform for developing, training, and deploying machine learning applications with managed notebooks, GPU machines, and deployment workflows. It serves ML developers, data scientists, researchers, and teams that need on-demand accelerated computing.

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vLLM preview
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vLLM

AI 推論平台

vLLM is an inference and serving engine for large language models, designed for high-throughput, memory-efficient deployment. It helps developers and infrastructure teams run open-source models through an OpenAI-compatible API across supported compute platforms.

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Bento preview
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Bento

AI 推論平台

Bento is an inference platform for packaging, deploying, optimizing, and operating AI and machine-learning models at scale. It supports open and custom models across cloud, on-premises, Kubernetes, and bring-your-own-cloud environments.

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FriendliAI preview
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FriendliAI

AI 推論平台

FriendliAI is an inference cloud for deploying frontier open-weight and custom AI models in production. It offers serverless Model APIs, dedicated GPU endpoints, and BYOG options for agent, multimodal, and other high-throughput workloads.

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CUDO Compute preview
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CUDO Compute

AI 模型部署

CUDO Compute designs, deploys, and operates dedicated NVIDIA GPU infrastructure for enterprise AI training and inference. It combines power-ready sites, cluster engineering, commissioning, and ongoing operational support for production workloads.

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Ray preview
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Ray

AI 推論平台

Ray is an open-source, Python-native framework for distributing and scaling AI, machine learning, and other compute-intensive workloads. It helps developers run workloads from a laptop to clusters with thousands of GPUs and supports data processing, training, serving, inference, and reinforcement learning.

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KServe preview
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KServe

AI 推論平台

KServe is a Kubernetes-based inference platform for deploying distributed generative and predictive AI workloads across multiple model frameworks. It is intended for teams that need a standardized way to run inference services in Kubernetes.

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