The generative AI (GenAI) market has seen explosive growth over the past 18 months, making the evaluation of large language models (LLMs) essential for enterprises – and against this backdrop, Google has emerged as the leader among the top LLM providers.
This is according to the latest “LLMs Competitive Landscape Assessment” report by leading analysts, GlobalData.
The research group identified the most significant large language models and researched, analysed, and scored them based on evaluation of six buying criteria. The report assesses and ranks the eight leading companies on the strength of their core model technology including context windows, multimodal and multilingual capabilities; vertical and horizontal use cases; AI Guardrails; ecosystem; professional services; and go-to-market strategies.
Google has been named “Leader”; OpenAI, Microsoft, and IBM have been ranked “Very Strong”; Amazon, Anthropic, and Meta have been ranked “Strong”; and Cohere is ranked as “Competitive”.
“Choosing the right large language model can be a challenging task for enterprises,” says Beatriz Valle, senior analyst, Enterprise Technology and Services at GlobalData. “The GenAI market is notoriously difficult to evaluate and the constant media coverage of improvements in model size, context windows, or performance benchmarks only adds to the confusion. Enterprise buyers must also look at other indicators. For example, whether a vendor has a clear strategy with practical use cases that drive a solid ROI (return on investment) on business applications.”
The GenAI market encompasses both big cloud computing providers such as Google, Microsoft and Amazon, and smaller startups vying for a seat at the table of the enterprise and B2B/B2C market including OpenAI, Anthropic and Cohere. The latter are playing a significant role in advancing generative AI technology and challenging Big Tech incumbents in the field, creating more customisable and agile models.
However, the established players are able to make the essential investments to cover high computing costs and have huge customer bases to deploy the technology via partnership ecosystems and professional services. They also have greater resources devoted to governance, data privacy, cybersecurity concerns, and ethical and legal considerations.
Charlotte Dunlap, research director: Enterprise Technology and Services at GlobalData, comments: “The world is witnessing the unfolding of an AI-driven economy – one which will redefine industries and revolutionise how humans live and work,” says Charlotte Dunlap, research director, Enterprise Technology and Services at GlobalData. “Yet enterprises, overwhelmed with the mega investments and explosive growth taking place in this newly emerging market, struggle to define their own strategies around LLM/GenAI.
“Enterprises need to answer the question: ‘What are the solutions in the generative AI market that are going to make a substantial difference in driving profitability and efficiencies?’ The new GlobalData Large Language Models – Competitive Landscape Assessment report helps them answer that,” says Dunlap.