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.

Qwen2.5-Omni-7B
Alibaba
Qwen2.5-Omni-7B is a multimodal language model developed by Alibaba. The model shows competitive results across 45 benchmarks. It excels particularly in DocVQA (95.2%), VocalSound (93.9%), GSM8k (88.7%). The model shows particular specialization in code tasks with an average performance of 76.0%. 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 Alibaba's latest advancement in AI technology.

Gemma 3 4B
2025-03-12

Qwen2.5-Omni-7B
Alibaba
2025-03-27
15 days newer
Performance Metrics
Context window and performance specifications

Gemma 3 4B

Qwen2.5-Omni-7B
Average performance across 10 common benchmarks

Gemma 3 4B

Qwen2.5-Omni-7B
Performance comparison across key benchmark categories

Gemma 3 4B

Qwen2.5-Omni-7B
Gemma 3 4B
2024-08-01
Provider Availability & Performance
Available providers and their performance metrics

Gemma 3 4B
DeepInfra

Qwen2.5-Omni-7B

Gemma 3 4B

Qwen2.5-Omni-7B