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

Gemma 3 12B
Gemma 3 12B is a multimodal language model developed by Google. It achieves strong performance with an average score of 63.8% across 26 benchmarks. It excels particularly in GSM8k (94.4%), IFEval (88.9%), DocVQA (87.1%). 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 12B
2025-03-12

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

Gemma 3 12B

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

Gemma 3 12B

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

Gemma 3 12B

Qwen2.5-Omni-7B
Provider Availability & Performance
Available providers and their performance metrics

Gemma 3 12B
DeepInfra

Qwen2.5-Omni-7B

Gemma 3 12B

Qwen2.5-Omni-7B