Testing the same prompt across multiple AI models without losing context — really interesting differences

I’ve been experimenting a lot with prompting lately, and one thing that kept slowing me down was switching between models to compare how each one responds.
So I started building a setup where I can switch between different LLMs (GPT, Claude, Grok, Gemini, etc.) inside the same chat thread, keeping the exact same context and prompt history.

It’s been fascinating to watch how differently each model handles the same prompt:
– some go heavy on structure
– some turn analytical
– some get way more creativehttps://10one-ai.com/
– some reinterpret the task entirely

Seeing these differences back-to-back on the same conversation feels like a new layer of “prompt engineering”:
instead of tweaking the prompt endlessly, you just swap the model and compare its bias, pattern, or reasoning style.

Curious if anyone here has tried something similar —
do you test your prompts across multiple models, or mostly stick to one?
And if you do compare, what differences have surprised you the most?https://10one-ai.com/https://10one-ai.com/ https://10one-ai.com/ https://10one-ai.com/https://10one-ai.com/https://10one-ai.com/

https://10one-ai.com/