Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

Google

Gemini 2.5 Pro

Google

Gemini 2.5 Pro is a multimodal language model developed by Google. It achieves strong performance with an average score of 67.1% across 16 benchmarks. It excels particularly in MRCR (93.0%), AIME 2024 (92.0%), Global-MMLU-Lite (88.6%). The model shows particular specialization in vision tasks with an average performance of 82.2%. With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Google's latest advancement in AI technology.

Microsoft

Phi-4-multimodal-instruct

Microsoft

Phi-4-multimodal-instruct is a multimodal language model developed by Microsoft. It achieves strong performance with an average score of 72.0% across 15 benchmarks. It excels particularly in ScienceQA Visual (97.5%), DocVQA (93.2%), MMBench (86.7%). The model shows particular specialization in general tasks with an average performance of 75.8%. It supports a 256K token context window for handling large documents. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Microsoft's latest advancement in AI technology.

Microsoft

Phi-4-multimodal-instruct

Microsoft

2025-02-01

Google

Gemini 2.5 Pro

Google

2025-05-20

3 months newer

Pricing Comparison

Cost per million tokens (USD)

Google

Gemini 2.5 Pro

Input:$1.25
Output:$10.00
Microsoft

Phi-4-multimodal-instruct

$11.10 cheaper
Input:$0.05
Output:$0.10

Performance Metrics

Context window and performance specifications

Google

Gemini 2.5 Pro

Larger context
Max Context:1.1M
Microsoft

Phi-4-multimodal-instruct

Max Context:256.0K
Parameters:5.6B

Average performance across 2 common benchmarks

Google

Gemini 2.5 Pro

+27.2%
Average Score:82.2%
Microsoft

Phi-4-multimodal-instruct

Average Score:55.0%

Performance comparison across key benchmark categories

Google

Gemini 2.5 Pro

vision
+12.5%
82.2%
general
69.4%
Microsoft

Phi-4-multimodal-instruct

vision
69.7%
general
+6.3%
75.8%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Phi-4-multimodal-instruct

2024-06-01

Gemini 2.5 Pro

2025-01-31

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemini 2.5 Pro

1 providers

Google

Throughput: 85 tok/s
Latency: 0.7ms
Microsoft

Phi-4-multimodal-instruct

1 providers

DeepInfra

Throughput: 25 tok/s
Latency: 0.5ms
Google

Gemini 2.5 Pro

+27.2%
Avg Score:82.2%
Providers:1
Microsoft

Phi-4-multimodal-instruct

Avg Score:55.0%
Providers:1