Google vs Microsoft

Google's 34-model portfolio reflects a fragmentation strategy with 15 open source variants and 9 free models, while Microsoft focuses on just 2 proprietary models (Phi 3.5 and Phi 4) scoring 25/100 and 32/100 respectively. This 17x model count difference means Google users face more decision complexity but gain access to specialized options like Gemini 2.5 Flash Lite Preview (60/100 score) for cost-sensitive deployments at $0.040/M tokens versus Microsoft's minimum $0.140/M.

Google's 79% vision coverage across models like Gemini 1.5 Pro and PaLM variants makes them the only viable choice for multimodal applications, while Microsoft's complete absence of vision capabilities limits Phi models to text-only use cases. This gap is particularly striking given that Google also maintains reasoning capabilities in 16/34 models (47%) while offering vision at prices starting from $0.040/M tokens.

Google's Gemini 2.5 Flash Lite Preview achieves 60/100 by leveraging 1M token context windows and multimodal capabilities, while Microsoft's Phi 4 peaks at 32/100 with only 66K context and no vision support. The average scores tell an even starker story: Google's 45/100 mean across 34 models versus Microsoft's 29/100 across just 2 models suggests Microsoft is competing on efficiency rather than raw capability.

Microsoft's 2 models integrate seamlessly with Azure AI services but cost 3.5x more at minimum ($0.140/M vs Google's $0.040/M) while lacking the vision, reasoning, and function calling features available in 16-27 of Google's 34 models. Azure-native teams requiring multimodal AI must either accept Google's integration overhead or wait for Microsoft to expand beyond text-only Phi models.

Google provides 9 free models including Gemma variants while Microsoft offers zero free options, forcing startups to pay $0.140-$0.620/M tokens from day one. Google's pricing spans a 300x range ($0.040-$12.00/M) enabling gradual scaling from free Gemma models to premium Gemini variants, whereas Microsoft's narrow 4.4x range ($0.140-$0.620/M) targets mid-tier enterprise deployments exclusively.