ChatGPT vs Gemini
OpenAI and Google both ship big model families, from flagship to pocket-sized. They overlap a lot and differ in the details. Here's how they tend to split, plus the live lineup Portail carries for each.
Give confident all-round answers, with reasoning-heavy o-series and Pro models at the top.
Be fast and cheap on Flash, handle very long inputs, and read images well.
Generate images on some models, reason on their bigger models, and write code.
Counts and limits from Portail's live model catalog.
Gemini Flash and Flash Lite are some of the cheapest capable models around, which makes them good for everyday questions and big batches of small tasks. GPT's Mini and Nano models fill the same role on OpenAI's side. The cost bands in the tables below show how fast each model uses credits.
Both families accept images on most models. Gemini is known for swallowing very long inputs; check the context column in the table for each model's limit. On Portail, long files are read in parts the model asks for, so even smaller windows can work through big documents.
Ask Gemini, switch to GPT, ask again. Same thread, same context, two answers to compare. Council does it in one step across up to six models.
It depends on the job. Gemini Flash is hard to beat on speed and price; GPT's top models are strong on hard reasoning. Run your own prompt through both to see.
Yes. Portail keeps one thread across every model, so you can switch between Gemini and GPT mid-conversation.
Gemini Flash Lite and GPT Nano sit at the cheap end of each family. The cost band column ($ to $$$$) shows the relative price of every model.
Every model, one thread, one memory. Free to start.