Model Comparison

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

Google

Gemini 2.0 Flash Thinking

Google

Gemini 2.0 Flash Thinking is a multimodal language model developed by Google. It achieves strong performance with an average score of 74.3% across 3 benchmarks. Notable strengths include MMMU (75.4%), GPQA (74.2%), AIME 2024 (73.3%). 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

Qwen2-VL-72B-Instruct

Alibaba

Qwen2-VL-72B-Instruct is a multimodal language model developed by Alibaba. It achieves strong performance with an average score of 75.8% across 15 benchmarks. It excels particularly in DocVQAtest (96.5%), VCR_en_easy (91.9%), ChartQA (88.3%). The model shows particular specialization in general tasks with an average performance of 82.2%. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents Alibaba's latest advancement in AI technology.

Alibaba

Qwen2-VL-72B-Instruct

Alibaba

2024-08-29

Google

Gemini 2.0 Flash Thinking

Google

2025-01-21

4 months newer

Performance comparison across key benchmark categories

Google

Gemini 2.0 Flash Thinking

general
73.8%
vision
+7.4%
75.4%
Alibaba

Qwen2-VL-72B-Instruct

general
+8.5%
82.2%
vision
68.0%
Knowledge Cutoff
Training data recency comparison

Qwen2-VL-72B-Instruct

2023-06-30

Gemini 2.0 Flash Thinking

2024-08-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemini 2.0 Flash Thinking

0 providers
Alibaba

Qwen2-VL-72B-Instruct

0 providers
Google

Gemini 2.0 Flash Thinking

Avg Score:0.0%
Providers:0
Alibaba

Qwen2-VL-72B-Instruct

Avg Score:0.0%
Providers:0