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

Gemma 3 4B
Gemma 3 4B is a multimodal language model developed by Google. The model shows competitive results across 26 benchmarks. It excels particularly in IFEval (90.2%), GSM8k (89.2%), DocVQA (75.8%). It supports a 262K 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 Google'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

Gemma 3 4B
2025-03-12
6 months newer
Performance Metrics
Context window and performance specifications

Gemma 3 4B

Qwen2-VL-72B-Instruct
Average performance across 3 common benchmarks

Gemma 3 4B

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

Gemma 3 4B

Qwen2-VL-72B-Instruct
Qwen2-VL-72B-Instruct
2023-06-30
Gemma 3 4B
2024-08-01
Provider Availability & Performance
Available providers and their performance metrics

Gemma 3 4B
DeepInfra

Qwen2-VL-72B-Instruct

Gemma 3 4B

Qwen2-VL-72B-Instruct