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

GPT-4.1 nano
OpenAI
GPT-4.1 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 25 benchmarks. It excels particularly in MMLU (80.1%), IFEval (74.5%), CharXiv-D (73.9%). 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 OpenAI's latest advancement in AI technology.

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.

Qwen2-VL-72B-Instruct
Alibaba
2024-08-29

GPT-4.1 nano
OpenAI
2025-04-14
7 months newer
Performance Metrics
Context window and performance specifications

GPT-4.1 nano

Qwen2-VL-72B-Instruct
Performance comparison across key benchmark categories

GPT-4.1 nano

Qwen2-VL-72B-Instruct
Qwen2-VL-72B-Instruct
2023-06-30
GPT-4.1 nano
2024-05-31
Provider Availability & Performance
Available providers and their performance metrics

GPT-4.1 nano
OpenAI

Qwen2-VL-72B-Instruct

GPT-4.1 nano

Qwen2-VL-72B-Instruct