Large Language Models (LLM): Competitive Landscape Assessment
Description
Large Language Models (LLM): Competitive Landscape Assessment
Summary
Evaluation of leading LLM vendors including OpenAI, Google, Microsoft, Amazon, Anthropic, IBM, Meta, Cohere and others, with market trends and enterprise buying criteria
Generative AI (GenAI) platforms are largely based on multimodal foundation models and LLMs; these are borne out of growing interest in accessing natural language processing (NLP) to query computers, following the significant advancements in AI seen in recent years. These include machine learning and deep learning via neural networks, also called generative adversarial networks (GANs), and also the emergence of the 'transformer' architecture in 2017, representing breakthrough efficiencies in training models. Further helping pave the way for LLMs has been the massive growth in computing power driven by graphic processing units (GPUs) with parallel processing capabilities to drive GenAI workloads.
Scope
Summary
Evaluation of leading LLM vendors including OpenAI, Google, Microsoft, Amazon, Anthropic, IBM, Meta, Cohere and others, with market trends and enterprise buying criteria
Generative AI (GenAI) platforms are largely based on multimodal foundation models and LLMs; these are borne out of growing interest in accessing natural language processing (NLP) to query computers, following the significant advancements in AI seen in recent years. These include machine learning and deep learning via neural networks, also called generative adversarial networks (GANs), and also the emergence of the 'transformer' architecture in 2017, representing breakthrough efficiencies in training models. Further helping pave the way for LLMs has been the massive growth in computing power driven by graphic processing units (GPUs) with parallel processing capabilities to drive GenAI workloads.
Scope
- Provides the most up-to-date competitive view of the LLM market, covering leading vendors, their 2025 launches, partnerships, and differentiating strategies across AI agents, multimodality, and governance.
- Links technology advancements, open-source disruptions, and enterprise buying criteria to real-world adoption needs, helping enterprises identify safe, scalable, and cost-effective LLM partners.
Table of Contents
26 Pages
- Large Language Models
- Report Summary:
- Product Class Scorecard
- Market Overview
- Market Assessment
- Market Drivers
- Buying Criteria
- Vendor Recommendations
- Buyer Recommendations
- Rated Competitors
- Contact Us
- List of Tables
- Table 1: Market Overview
- Table 2: Rated Competitors
- List of Figures
- Figure 1: Product Class Scorecard
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