Comparing AI for web creation - one prompt, 11 models, vastly different results

Proprietary models (Claude, GPT, Gemini) traditionally offer better quality and nuance understanding but have higher costs. Open-source models (DeepSeek, Kimi) are cheaper and faster with improved optimization, but may underperform on complex scenarios. Recently, open-source model quality is rapidly catching up.

Selection depends on combining factors: cost (credits), processing speed, output quality, and specific capabilities (database work, images, etc.). Simple tasks need only cheaper models, while complex scenarios justify higher-cost options. Ideally, an intelligent router would automatically pick the optimal model.

Use intelligent routing that selects models by task complexity—cheaper models for simple operations, powerful ones only when necessary. Prompt optimization helps models work more efficiently. Another option is choosing appropriate effort levels if the model supports it.