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.

Alibaba

QvQ-72B-Preview

Alibaba

QvQ-72B-Preview is a multimodal language model developed by Alibaba. The model shows competitive results across 4 benchmarks. Notable strengths include MathVista (71.4%), MMMU (70.3%), MathVision (35.9%). 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 2024, it represents Alibaba's latest advancement in AI technology.

Alibaba

QvQ-72B-Preview

Alibaba

2024-12-25

Google

Gemini 2.5 Pro

Google

2025-05-20

4 months newer

Performance Metrics

Context window and performance specifications

Google

Gemini 2.5 Pro

Larger context
Max Context:1.1M
Alibaba

QvQ-72B-Preview

Max Context:-
Parameters:73.4B

Average performance across 1 common benchmarks

Google

Gemini 2.5 Pro

+9.3%
Average Score:79.6%
Alibaba

QvQ-72B-Preview

Average Score:70.3%

Performance comparison across key benchmark categories

Google

Gemini 2.5 Pro

vision
+11.9%
82.2%
general
+49.0%
69.4%
Alibaba

QvQ-72B-Preview

vision
70.3%
general
20.4%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

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
Alibaba

QvQ-72B-Preview

0 providers
Google

Gemini 2.5 Pro

+9.3%
Avg Score:79.6%
Providers:1
Alibaba

QvQ-72B-Preview

Avg Score:70.3%
Providers:0