Multi Horse Race
“Multi Horse Race” refers to an evaluation of the large language model landscape as of mid-2025, presented by Dave Plummer, a retired Microsoft software engineer. The assessment examines the competitive state of leading LLM systems during this period, drawing on hands-on experience with the major offerings available at that time. Rather than identifying a clear winner, the evaluation characterizes the market as genuinely competitive, with multiple systems offering distinct strengths and trade-offs.
Context and Approach
Plummer’s evaluation reflects the perspective of someone with deep technical experience in software engineering, providing practical insights into how different LLMs performed across real-world use cases. The “multi horse race” framing acknowledges that no single LLM had achieved clear dominance across all dimensions of capability, cost, speed, and specialized performance by mid-2025.
Implications
The analysis suggests that the LLM market remained segmented rather than consolidated, with different systems better suited to different applications and user needs. This competitive landscape had implications for users selecting models, organizations deploying AI systems, and the broader trajectory of AI development.