TODO for AI
vs ChatGPT
The default AI assistant, with agent mode, deep research and connectors bolted onto the chat product. Here is where each one wins, with numbers, and who should pick which.
OpenAI only
Every providerWho should pick which
- You mainly want an excellent assistant for chat, writing and research
- You want the lowest entry price at $8
- You never need it to touch your own machine or code
- You want the work executed on your PC and a cloud VM, not just described to you
- You want Claude, Gemini and GPT in one place, reviewing each other
- You need a persistent machine with your logins, secrets and scheduled runs
- You want one budget across every capability instead of a cap per feature
What ChatGPT is, and where it stops
ChatGPT is the product everyone measures assistants against, and for chat, research and writing it deserves that. Agent mode and deep research turned it from a text box into something that goes away and comes back with work done, connectors reach into Drive and mail, and at $8 for Go the entry price is the lowest here. As a general assistant it is the safest default on the list.
It is still a chat product with agents attached. Everything runs on OpenAI models inside OpenAI's sandbox, and each capability carries its own quota, so you run out of deep research while your message allowance sits untouched. Agent mode can keep cookies between runs and schedule recurring tasks, but it does so inside OpenAI's environment: it never opens a terminal on your machine, never picks up a CLI tool you installed, and never uses the Chrome profile your real sessions live in.
Anyone who wants one excellent assistant for research, writing and everyday questions.
Three reasons ChatGPT users look elsewhere
Messages, deep research, agent runs and images each have a separate cap. You hit one and the rest of the plan cannot cover for it.
Agent mode browses in OpenAI's environment and keeps its own sessions there. It is still not a shell on your PC, not your Chrome profile, and not your repo.
Every answer comes from OpenAI models. There is no way to have Claude or Gemini review the output before it ships.
Six dimensions that decide it
What each one ships
Same ladder, different meter
A separate cap per feature: messages, deep research runs, agent runs, image generation. Nothing is pooled between them and nothing carries over.
One pool priced in dollars of model cost, spendable on any vendor. Session and weekly windows pace it, and a 1.3-1.5x plan multiplier applies, so a $20 plan is about $15 of list-price API. Team seat prices go into one shared pool.