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市場調查報告書
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2111071

人工智慧模型服務市場預測至2034年—按組件、部署模式、模型類型、服務架構、應用、最終用戶和地區分類的全球分析

AI Model Serving Market Forecasts to 2034 - Global Analysis By Component (Software Platforms, Managed Services, and Professional Services), Deployment Mode, Model Type, Serving Framework, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，全球 AI 模型服務市場預計將在 2026 年達到 29 億美元，到 2034 年達到 176 億美元，預測期內複合年成長率為 25.3%。

AI模型服務平台是一個綜合解決方案，使組織能夠在生產環境中部署、管理、擴展和監控已訓練的建議模型。這些平台包括軟體平台、託管服務和專業服務，並支援多種模型類型，包括大規模語言模型、小規模語言模型、多模態模型。它們透過即時、批次、無伺服器和基於Kubernetes的服務框架進行部署。這項技術使組織能夠有效率地運作AI模型，確保可靠的效能，並從其AI投資中獲得價值。

將人工智慧和模型應用於生產環境的需求日益成長

對人工智慧及其模型在生產環境中的應用日益成長的需求，是推動人工智慧模型服務市場發展的主要動力。各組織正逐步超越人工智慧的實驗階段，將模型部署到能夠創造商業價值的生產環境。模型服務平台為人工智慧的可靠、大規模運作提供了必要的基礎設施。隨著對高效率模型部署和管理的需求不斷成長，模型服務平台的普及速度也正在加快。隨著人工智慧在業務運作中扮演越來越重要的角色，對模型服務解決方案的需求也將持續成長。

高昂的基礎設施成本和營運複雜性

高昂的基礎設施成本和營運複雜性阻礙了人工智慧模型服務市場的成長。大規模部署和管理人工智慧模型需要對基礎設施、監控和專業知識進行大量投資。企業在確保可靠性、性能和成本效益方面面臨許多挑戰。支援各種模型類型和框架的複雜性進一步加重了營運負擔。這些成本和複雜性限制可能會阻礙人工智慧模型服務的應用，尤其對於中小企業而言。

針對邊緣和即時服務的最佳化

邊緣和即時服務的最佳化為人工智慧模型服務市場帶來了巨大的機會。邊緣服務能夠為需要即時回應的應用提供低延遲推理。即時服務功能則支援互動式人工智慧應用。模型最佳化和輕量級服務框架的進步使得邊緣和即時部署變得越來越可行。隨著人工智慧應用擴展到邊緣環境，對最佳化服務解決方案的需求持續成長，為創新供應商創造了巨大的發展機會。

快速發展的AI模型與服務框架

人工智慧模型和服務框架的快速發展對人工智慧模型服務市場構成了重大威脅。人工智慧模型的規模和複雜性不斷成長，需要對服務基礎設施進行持續更新。服務框架也在快速演進，帶來相容性挑戰。企業可能難以跟上這些變化。這些挑戰可能會影響服務平台的價值和普及程度。

新型冠狀病毒（COVID-19）的影響：

新冠疫情加速了人工智慧模型服務平台的普及，各組織機構迅速部署人工智慧應用，以支援遠距辦公、客戶參與和提升營運效率。數位化互動的激增催生了對可擴展模型服務基礎設施的需求。各組織機構都認知到可靠部署人工智慧的重要性。在後疫情時代，這些平台已成為人工智慧主導業務運作的必備工具。

在預測期內，軟體平台細分市場預計將佔據最大的市場佔有率。

預計在預測期內，軟體平台細分市場將佔據最大的市場佔有率，這主要得益於綜合服務平台在生產環境中部署、管理和擴展人工智慧模型方面發揮的關鍵作用。軟體平台提供大規模、可靠運作人工智慧所需的工具和基礎設施。對整合式、生產就緒型解決方案日益成長的需求也鞏固了主導地位。

預計在預測期內，雲端運算領域將呈現最高的複合年成長率。

在預測期內，由於雲端模型服務的擴充性、柔軟性和成本效益，雲端細分市場預計將呈現最高的成長率。雲端平台使企業能夠按需擴展服務容量，而無需大量前期投資。與雲端人工智慧服務的整合簡化了部署。隨著企業採用「雲端優先」的人工智慧策略，雲端模型服務的應用預計將持續擴大。

市佔率最大的地區：

在預測期內，北美預計將佔據最大的市場佔有率，這主要得益於其在人工智慧創新領域的大量投資、對先進技術的早期應用以及領先服務平台提供商的存在。該地區專注於在生產環境中實現人工智慧的營運和部署，從而催生了對綜合服務解決方案的需求。大量的技術投資以及對透過人工智慧實現價值的堅定承諾，鞏固了其市場主導地位。

複合年成長率最高的地區：

在預測期內，亞太地區預計將呈現最高的複合年成長率，這主要得益於人工智慧的快速普及、科技產業的擴張以及主要經濟體對人工智慧基礎設施投資的增加。中國、印度和日本等國家在人工智慧應用和模型服務方面正經歷顯著成長。各國政府為促進人工智慧創新和數位轉型所採取的措施也進一步推動了該地區的市場擴張。

免費客製化服務：

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  • 企業概況
    • 對其他市場參與者（最多 3 家公司）進行全面分析
    • 對主要公司進行SWOT分析（最多3家公司）
  • 區域細分
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    • 根據產品系列、地理覆蓋範圍和策略聯盟對領先公司進行基準分析。

目錄

第1章執行摘要

  • 市場概覽及主要亮點
  • 促進因素、挑戰與機遇
  • 競爭格局概述
  • 戰略洞察與建議

第2章：研究框架

  • 研究目標和範圍
  • 相關人員分析
  • 研究假設和限制
  • 調查方法

第3章 市場動態與趨勢分析

  • 市場定義與結構
  • 主要市場促進因素
  • 市場限制與挑戰
  • 投資成長機會和重點領域
  • 產業威脅與風險評估
  • 技術與創新展望
  • 新興市場/高成長市場
  • 監管和政策環境
  • 新冠疫情的影響及復甦前景

第4章：競爭環境與策略評估

  • 波特五力分析
    • 供應商的議價能力
    • 買方的議價能力
    • 替代品的威脅
    • 新進入者的威脅
    • 競爭公司之間的競爭
  • 主要公司市佔率分析
  • 產品基準評效和效能比較

第5章：全球人工智慧模型服務市場：按組件分類

  • 軟體平台
  • 託管服務
  • 專業服務

第6章 全球人工智慧模型服務市場：依部署模式分類

  • 雲
  • 現場
  • 混合
  • 邊緣

第7章 全球人工智慧模型服務市場：依模型類型分類

  • 大規模語言模型（LLM）
  • 小型語言模型（SLM）
  • 電腦視覺模型
  • 語音/音訊模型
  • 建議模型
  • 預測分析模型
  • 多模態模型

第8章：全球人工智慧模型服務市場：按服務框架分類

  • 即時（線上）模型服務
  • 大量式服務模式
  • 無伺服器模型服務
  • 基於 Kubernetes 的模式服務

第9章 全球人工智慧模型服務市場：按應用分類

  • 生成式人工智慧的應用領域
  • 自然語言處理（NLP）
  • 電腦視覺
  • 語音辨識與合成
  • 建議引擎
  • 詐欺偵測和風險分析
  • 預測性保護
  • 自主系統

第10章：全球人工智慧模型服務市場：以最終用戶分類

  • BFSI
  • 醫療保健和生命科學
  • 零售與電子商務
  • 製造業
  • IT/通訊
  • 汽車和運輸業
  • 政府/公共部門
  • 媒體與娛樂
  • 能源公用事業

第11章 全球人工智慧模型服務市場：按地區分類

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 荷蘭
    • 比利時
    • 瑞典
    • 瑞士
    • 波蘭
    • 其他歐洲國家
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 泰國
    • 馬來西亞
    • 新加坡
    • 越南
    • 其他亞太國家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥倫比亞
    • 智利
    • 秘魯
    • 其他南美國家
  • 世界其他地區（RoW）
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 卡達
      • 以色列
      • 其他中東國家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲國家

第12章 策略市場資訊

  • 工業價值網路和供應鏈評估
  • 空白區域和機會地圖
  • 產品演進與市場生命週期分析
  • 通路、經銷商和打入市場策略的評估

第13章 產業趨勢與策略舉措

  • 併購
  • 夥伴關係、聯盟和合資企業
  • 新產品發布和認證
  • 擴大生產能力和投資
  • 其他策略舉措

第14章：公司簡介

  • NVIDIA
  • Google
  • Amazon Web Services（AWS）
  • Microsoft
  • IBM
  • Oracle
  • Databricks
  • Red Hat
  • DataRobot
  • Hugging Face
  • Anyscale
  • BentoML
  • Predibase
  • VMware
  • Domino Data Lab
Product Code: SMRC38771

According to Stratistics MRC, the Global AI Model Serving Market is accounted for $2.9 billion in 2026 and is expected to reach $17.6 billion by 2034, growing at a CAGR of 25.3% during the forecast period. AI Model Serving Platforms are comprehensive solutions that enable organizations to deploy, manage, scale, and monitor trained artificial intelligence models in production environments. These platforms encompass software platforms, managed services, and professional services, supporting various model types including large language models, small language models, computer vision models, speech and audio models, recommendation models, predictive analytics models, and multimodal models deployed through real-time, batch, serverless, and Kubernetes-based serving frameworks. This technology helps organizations operationalize AI models efficiently, ensure reliable performance, and deliver value from AI investments.

Market Dynamics:

Driver:

Growing demand for production AI and model operationalization

The increasing demand for production AI and model operationalization serves as a primary driver for the AI Model Serving market. Organizations are moving beyond AI experimentation to deploy models in production environments where they deliver business value. Model serving platforms provide the infrastructure needed to operationalize AI reliably and at scale. The need for efficient model deployment and management accelerates adoption. As AI becomes central to business operations, the demand for model serving solutions continues to grow.

Restraint:

High infrastructure costs and operational complexity

The significant infrastructure costs and operational complexity pose restraints to the AI Model Serving market. Deploying and managing AI models at scale requires substantial investment in infrastructure, monitoring, and expertise. Organizations face challenges in ensuring reliability, performance, and cost efficiency. The complexity of serving diverse model types and frameworks adds to operational burden. These cost and complexity constraints can limit adoption, particularly among smaller organizations.

Opportunity:

Optimization for edge and real-time serving

The optimization for edge and real-time serving presents significant opportunities for the AI Model Serving market. Edge serving enables low-latency inference for applications requiring immediate responses. Real-time serving capabilities support interactive AI applications. Advances in model optimization and lightweight serving frameworks make edge and real-time deployment increasingly viable. As AI applications expand to edge environments, the demand for optimized serving solutions continues to grow, creating substantial opportunities for innovative providers.

Threat:

Rapidly evolving AI models and serving frameworks

The rapidly evolving AI models and serving frameworks pose significant threats to the AI Model Serving market. AI models grow larger and more complex continuously, requiring ongoing updates to serving infrastructure. Serving frameworks evolve rapidly, creating compatibility challenges. Organizations may struggle to keep pace with changes. These challenges can affect the value and adoption of serving platforms.

Covid-19 Impact:

The COVID-19 pandemic accelerated the adoption of AI model serving platforms as organizations rapidly deployed AI applications for remote work, customer engagement, and operational efficiency. The surge in digital interactions created demand for scalable model serving infrastructure. Organizations recognized the importance of reliable AI deployment. Post-pandemic, these platforms have become essential for AI-driven business operations.

The software platforms segment is expected to be the largest during the forecast period

The software platforms segment is expected to account for the largest market share during the forecast period, driven by the essential role of comprehensive serving platforms in deploying, managing, and scaling AI models in production. Software platforms provide the tools and infrastructure needed to operationalize AI reliably at scale. The increasing demand for integrated, production-ready solutions supports market leadership.

The cloud segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the cloud segment is predicted to witness the highest growth rate, due to the scalability, flexibility, and cost-effectiveness of cloud-based model serving. Cloud platforms enable organizations to scale serving capacity on demand without significant upfront investment. The integration with cloud AI services simplifies deployment. As organizations embrace cloud-first AI strategies, cloud model serving continues to gain adoption.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, driven by substantial investment in AI innovation, early adoption of advanced technologies, and the presence of major serving platform providers. The region's focus on AI operationalization and production deployment creates demand for comprehensive serving solutions. Significant technology spending and the emphasis on AI value realization contribute to market leadership.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, fueled by rapid AI adoption, expanding technology sectors, and growing investment in AI infrastructure across major economies. Countries such as China, India, and Japan are witnessing significant growth in AI deployment and model serving adoption. Government initiatives promoting AI innovation and digital transformation further contribute to regional market expansion.

Key players in the market

Some of the key players in the AI Model Serving Market include NVIDIA Corporation, Google LLC, Amazon Web Services (AWS), Microsoft Corporation, IBM Corporation, Oracle Corporation, Databricks Inc., Red Hat Inc., DataRobot Inc., Hugging Face, Anyscale Inc., BentoML, Predibase, VMware Inc., and Domino Data Lab.

Key Developments:

In March 2026, NVIDIA announced the launch of a new AI model serving platform featuring optimized support for large language models and generative AI. The platform delivers high-performance serving with reduced latency and improved cost efficiency for enterprise AI deployments.

In February 2026, Google introduced enhanced model serving capabilities with improved auto-scaling and model versioning features. The enhancements enable efficient, reliable serving across diverse AI applications and frameworks.

Components Covered:

  • Software Platforms
  • Managed Services
  • Professional Services

Deployment Modes Covered:

  • Cloud
  • On-Premises
  • Hybrid
  • Edge

Model Types Covered:

  • Large Language Models (LLMs)
  • Small Language Models (SLMs)
  • Computer Vision Models
  • Speech & Audio Models
  • Recommendation Models
  • Predictive Analytics Models
  • Multimodal Models

Serving Frameworks Covered:

  • Real-Time (Online) Model Serving
  • Batch Model Serving
  • Serverless Model Serving
  • Kubernetes-Based Model Serving

Applications Covered:

  • Generative AI Applications
  • Natural Language Processing (NLP)
  • Computer Vision
  • Speech Recognition & Synthesis
  • Recommendation Engines
  • Fraud Detection & Risk Analytics
  • Predictive Maintenance
  • Autonomous Systems

End Users Covered:

  • BFSI
  • Healthcare & Life Sciences
  • Retail & E-commerce
  • Manufacturing
  • IT & Telecommunications
  • Automotive & Transportation
  • Government & Public Sector
  • Media & Entertainment
  • Energy & Utilities

Regions Covered:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Belgium
    • Sweden
    • Switzerland
    • Poland
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Thailand
    • Malaysia
    • Singapore
    • Vietnam
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Chile
    • Peru
    • Rest of South America
  • Rest of the World (RoW)
    • Middle East
  • Saudi Arabia
  • United Arab Emirates
  • Qatar
  • Israel
  • Rest of Middle East
    • Africa
  • South Africa
  • Egypt
  • Morocco
  • Rest of Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2023, 2024, 2025, 2026, 2027, 2028, 2030, 2032 and 2034
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global AI Model Serving Market, By Component

  • 5.1 Software Platforms
  • 5.2 Managed Services
  • 5.3 Professional Services

6 Global AI Model Serving Market, By Deployment Mode

  • 6.1 Cloud
  • 6.2 On-Premises
  • 6.3 Hybrid
  • 6.4 Edge

7 Global AI Model Serving Market, By Model Type

  • 7.1 Large Language Models (LLMs)
  • 7.2 Small Language Models (SLMs)
  • 7.3 Computer Vision Models
  • 7.4 Speech & Audio Models
  • 7.5 Recommendation Models
  • 7.6 Predictive Analytics Models
  • 7.7 Multimodal Models

8 Global AI Model Serving Market, By Serving Framework

  • 8.1 Real-Time (Online) Model Serving
  • 8.2 Batch Model Serving
  • 8.3 Serverless Model Serving
  • 8.4 Kubernetes-Based Model Serving

9 Global AI Model Serving Market, By Application

  • 9.1 Generative AI Applications
  • 9.2 Natural Language Processing (NLP)
  • 9.3 Computer Vision
  • 9.4 Speech Recognition & Synthesis
  • 9.5 Recommendation Engines
  • 9.6 Fraud Detection & Risk Analytics
  • 9.7 Predictive Maintenance
  • 9.8 Autonomous Systems

10 Global AI Model Serving Market, By End User

  • 10.1 BFSI
  • 10.2 Healthcare & Life Sciences
  • 10.3 Retail & E-commerce
  • 10.4 Manufacturing
  • 10.5 IT & Telecommunications
  • 10.6 Automotive & Transportation
  • 10.7 Government & Public Sector
  • 10.8 Media & Entertainment
  • 10.9 Energy & Utilities

11 Global AI Model Serving Market, By Geography

  • 11.1 North America
    • 11.1.1 United States
    • 11.1.2 Canada
    • 11.1.3 Mexico
  • 11.2 Europe
    • 11.2.1 United Kingdom
    • 11.2.2 Germany
    • 11.2.3 France
    • 11.2.4 Italy
    • 11.2.5 Spain
    • 11.2.6 Netherlands
    • 11.2.7 Belgium
    • 11.2.8 Sweden
    • 11.2.9 Switzerland
    • 11.2.10 Poland
    • 11.2.11 Rest of Europe
  • 11.3 Asia Pacific
    • 11.3.1 China
    • 11.3.2 Japan
    • 11.3.3 India
    • 11.3.4 South Korea
    • 11.3.5 Australia
    • 11.3.6 Indonesia
    • 11.3.7 Thailand
    • 11.3.8 Malaysia
    • 11.3.9 Singapore
    • 11.3.10 Vietnam
    • 11.3.11 Rest of Asia Pacific
  • 11.4 South America
    • 11.4.1 Brazil
    • 11.4.2 Argentina
    • 11.4.3 Colombia
    • 11.4.4 Chile
    • 11.4.5 Peru
    • 11.4.6 Rest of South America
  • 11.5 Rest of the World (RoW)
    • 11.5.1 Middle East
      • 11.5.1.1 Saudi Arabia
      • 11.5.1.2 United Arab Emirates
      • 11.5.1.3 Qatar
      • 11.5.1.4 Israel
      • 11.5.1.5 Rest of Middle East
    • 11.5.2 Africa
      • 11.5.2.1 South Africa
      • 11.5.2.2 Egypt
      • 11.5.2.3 Morocco
      • 11.5.2.4 Rest of Africa

12 Strategic Market Intelligence

  • 12.1 Industry Value Network and Supply Chain Assessment
  • 12.2 White-Space and Opportunity Mapping
  • 12.3 Product Evolution and Market Life Cycle Analysis
  • 12.4 Channel, Distributor, and Go-to-Market Assessment

13 Industry Developments and Strategic Initiatives

  • 13.1 Mergers and Acquisitions
  • 13.2 Partnerships, Alliances, and Joint Ventures
  • 13.3 New Product Launches and Certifications
  • 13.4 Capacity Expansion and Investments
  • 13.5 Other Strategic Initiatives

14 Company Profiles

  • 14.1 NVIDIA
  • 14.2 Google
  • 14.3 Amazon Web Services (AWS)
  • 14.4 Microsoft
  • 14.5 IBM
  • 14.6 Oracle
  • 14.7 Databricks
  • 14.8 Red Hat
  • 14.9 DataRobot
  • 14.10 Hugging Face
  • 14.11 Anyscale
  • 14.12 BentoML
  • 14.13 Predibase
  • 14.14 VMware
  • 14.15 Domino Data Lab

List of Tables

  • Table 1 Global AI Model Serving Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global AI Model Serving Market Outlook, By Component (2023-2034) ($MN)
  • Table 3 Global AI Model Serving Market Outlook, By Software Platforms (2023-2034) ($MN)
  • Table 4 Global AI Model Serving Market Outlook, By Managed Services (2023-2034) ($MN)
  • Table 5 Global AI Model Serving Market Outlook, By Professional Services (2023-2034) ($MN)
  • Table 6 Global AI Model Serving Market Outlook, By Deployment Mode (2023-2034) ($MN)
  • Table 7 Global AI Model Serving Market Outlook, By Cloud (2023-2034) ($MN)
  • Table 8 Global AI Model Serving Market Outlook, By On-Premises (2023-2034) ($MN)
  • Table 9 Global AI Model Serving Market Outlook, By Hybrid (2023-2034) ($MN)
  • Table 10 Global AI Model Serving Market Outlook, By Edge (2023-2034) ($MN)
  • Table 11 Global AI Model Serving Market Outlook, By Model Type (2023-2034) ($MN)
  • Table 12 Global AI Model Serving Market Outlook, By Large Language Models (LLMs) (2023-2034) ($MN)
  • Table 13 Global AI Model Serving Market Outlook, By Small Language Models (SLMs) (2023-2034) ($MN)
  • Table 14 Global AI Model Serving Market Outlook, By Computer Vision Models (2023-2034) ($MN)
  • Table 15 Global AI Model Serving Market Outlook, By Speech & Audio Models (2023-2034) ($MN)
  • Table 16 Global AI Model Serving Market Outlook, By Recommendation Models (2023-2034) ($MN)
  • Table 17 Global AI Model Serving Market Outlook, By Predictive Analytics Models (2023-2034) ($MN)
  • Table 18 Global AI Model Serving Market Outlook, By Multimodal Models (2023-2034) ($MN)
  • Table 19 Global AI Model Serving Market Outlook, By Serving Framework (2023-2034) ($MN)
  • Table 20 Global AI Model Serving Market Outlook, By Real-Time (Online) Model Serving (2023-2034) ($MN)
  • Table 21 Global AI Model Serving Market Outlook, By Batch Model Serving (2023-2034) ($MN)
  • Table 22 Global AI Model Serving Market Outlook, By Serverless Model Serving (2023-2034) ($MN)
  • Table 23 Global AI Model Serving Market Outlook, By Kubernetes-Based Model Serving (2023-2034) ($MN)
  • Table 24 Global AI Model Serving Market Outlook, By Application (2023-2034) ($MN)
  • Table 25 Global AI Model Serving Market Outlook, By Generative AI Applications (2023-2034) ($MN)
  • Table 26 Global AI Model Serving Market Outlook, By Natural Language Processing (NLP) (2023-2034) ($MN)
  • Table 27 Global AI Model Serving Market Outlook, By Computer Vision (2023-2034) ($MN)
  • Table 28 Global AI Model Serving Market Outlook, By Speech Recognition & Synthesis (2023-2034) ($MN)
  • Table 29 Global AI Model Serving Market Outlook, By Recommendation Engines (2023-2034) ($MN)
  • Table 30 Global AI Model Serving Market Outlook, By Fraud Detection & Risk Analytics (2023-2034) ($MN)
  • Table 31 Global AI Model Serving Market Outlook, By Predictive Maintenance (2023-2034) ($MN)
  • Table 32 Global AI Model Serving Market Outlook, By Autonomous Systems (2023-2034) ($MN)
  • Table 33 Global AI Model Serving Market Outlook, By End User (2023-2034) ($MN)
  • Table 34 Global AI Model Serving Market Outlook, By BFSI (2023-2034) ($MN)
  • Table 35 Global AI Model Serving Market Outlook, By Healthcare & Life Sciences (2023-2034) ($MN)
  • Table 36 Global AI Model Serving Market Outlook, By Retail & E-commerce (2023-2034) ($MN)
  • Table 37 Global AI Model Serving Market Outlook, By Manufacturing (2023-2034) ($MN)
  • Table 38 Global AI Model Serving Market Outlook, By IT & Telecommunications (2023-2034) ($MN)
  • Table 39 Global AI Model Serving Market Outlook, By Automotive & Transportation (2023-2034) ($MN)
  • Table 40 Global AI Model Serving Market Outlook, By Government & Public Sector (2023-2034) ($MN)
  • Table 41 Global AI Model Serving Market Outlook, By Media & Entertainment (2023-2034) ($MN)
  • Table 42 Global AI Model Serving Market Outlook, By Energy & Utilities (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) are also represented in the same manner as above.