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.

Qwen3-235B-A22B-Instruct-2507

Alibaba

Qwen3-235B-A22B-Instruct-2507 is a language model developed by Alibaba. It achieves strong performance with an average score of 72.1% across 25 benchmarks. It excels particularly in ZebraLogic (95.0%), MMLU-Redux (93.1%), IFEval (88.7%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba's latest advancement in AI technology.