Model Comparison

Llama 4 Scout

Meta

Llama 4 Scout is a multimodal language model developed by Meta. It achieves strong performance with an average score of 67.3% across 12 benchmarks. It excels particularly in DocVQA (94.4%), MGSM (90.6%), ChartQA (88.8%). The model shows particular specialization in vision tasks with an average performance of 81.9%. With a 20.0M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 6 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Meta'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.