Google (29 models) vs Microsoft (3 models) - compared across composite scores, pricing, capabilities, and context windows.
| Score | vs | Microsoft | Score | |
|---|---|---|---|---|
| Gemini 3 Flash Preview | 88 | Phi 4 | 60 | |
| Gemini 2.5 Pro | 84 | Phi 4 Mini Instruct | 53 | |
| Gemini 2.5 Pro Preview 06-05 | 84 | WizardLM-2 8x22B | 28 |
| Capability | Microsoft | Leader | |
|---|---|---|---|
Vision | 25/29 | 0/3 | |
Reasoning | 17/29 | 0/3 | |
Function Calling | 19/29 | 0/3 | |
JSON Mode | 26/29 | 2/3 | |
Web Search | 16/29 | 0/3 | |
Streaming | 27/29 | 3/3 | |
Image Output | 4/29 | 0/3 |
| Metric | Microsoft | |
|---|---|---|
| Cheapest Input (per 1M tokens) | $0.040 Gemma 3 4B | $0.065 Phi 4 |
| Cheapest Output (per 1M tokens) | $0.080 | $0.140 |
| Most Expensive Input (per 1M tokens) | $2.00 Gemini 3.1 Pro Preview Custom Tools | $0.620 WizardLM-2 8x22B |
| Most Expensive Output (per 1M tokens) | $12.00 | $0.620 |
| Free Models | 4 | 0 |
| Max Context Window | 1.0M | 128K |
| Model | Score | Input $/M | Output $/M |
|---|---|---|---|
| Gemini 3 Flash Preview | 88 | $0.500 | $3.00 |
| Gemini 2.5 Pro | 84 | $1.25 | $10.00 |
| Gemini 2.5 Pro Preview 06-05 | 84 | $1.25 | $10.00 |
| Gemini 2.5 Pro Preview 05-06 | 84 | $1.25 | $10.00 |
| Gemini 3.1 Pro Preview Custom Tools | 81 | $2.00 | $12.00 |
| Gemini 3.1 Pro Preview | 81 | $2.00 | $12.00 |
| Gemma 4 31B (free) | 81 | Free | Free |
| Gemma 4 31B | 81 | $0.130 | $0.380 |
| Gemini 3.1 Flash Lite Preview | 80 | $0.250 | $1.50 |
| Gemini 2.5 Flash Lite Preview 09-2025 | 79 | $0.100 | $0.400 |
| Gemini 2.5 Flash Lite | 79 | $0.100 | $0.400 |
| Gemini 2.5 Flash | 79 | $0.300 | $2.50 |
| Gemma 2 27B | 77 | $0.650 | $0.650 |
| Gemma 4 26B A4B (free) | 73 | Free | Free |
| Gemma 4 26B A4B | 73 | $0.060 | $0.330 |
| Gemini 2.0 Flash | 72 | $0.100 | $0.400 |
| Gemini 2.0 Flash Lite | 59 | $0.075 | $0.300 |
| Lyria 3 Pro Preview | 40 | Free | Free |
| Lyria 3 Clip Preview | 40 | Free | Free |
| Gemma 3n 4B | 40 | $0.060 | $0.120 |
| Model | Score | Input $/M | Output $/M |
|---|---|---|---|
| Phi 4 | 60 | $0.065 | $0.140 |
| Phi 4 Mini Instruct | 53 | $0.080 | $0.350 |
| WizardLM-2 8x22B | 28 | $0.620 | $0.620 |
Compare any two AI providers side-by-side.
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.
Microsoft open sources 100% of their portfolio (both Phi models) but with mediocre scores of 25-32/100, while Google open sources 44% (15/34 models) including higher-performing Gemma and T5 variants. Google's selective approach preserves commercial advantage in their top-tier Gemini models (60/100) while Microsoft's all-in open source strategy suggests they're prioritizing ecosystem adoption over direct model monetization.