A ChatGPT subscription starts at $20 a month and is one of the cheapest ways to run inference. OpenAI has also been fairly relaxed lately about third-party agents using them, which makes the deal even better for a lot of us.
But a subscription can't be used as freely as pay-per-token access, and the providers police the difference. Anthropic recently narrowed its subscriptions to first-party apps; OpenAI has its own limits. Here's what will get you banned from an OpenAI subscription.
Sharing your subscription
A ChatGPT subscription is strictly personal. One subscription, one user. Sharing yours breaks OpenAI's terms of service.
That also covers account pooling and account rotation, where several people share the same credentials to dodge rate limits.
Running it in automation
Automation (CI, runners, schedulers) should run on per-token pricing, not a subscription. Once a system calls the OpenAI API with your token while you're not in the loop, the usage stops being personal. No unattended production system should run on a ChatGPT subscription.
Serving other users
For now, you can point an autonomous agent like OpenClaw or Hermes at your ChatGPT subscription, as long as it only talks to you.
The moment that agent starts chatting with other people, or serving them in any way, it turns into a team use case, and that inference should be paid per usage.
Putting it in a commercial product
Same logic here. Making an LLM call authenticated with an individual ChatGPT subscription inside a product you ship breaks OpenAI's terms.
That access is subsidized, and reselling it in any form isn't what it's meant for. If you've built something just for yourself and you're the only user, you're probably fine.
The bottom line
A ChatGPT subscription is personal. Anything that stretches past personal use can get you restricted or banned. If you're not sure your usage counts, move it to pay-as-you-go.
If you want to keep the subscription for your own work and fall back to per-token pricing for everything else, that's what Manifest is built for. It connects your subscriptions and your API keys in one place and routes each request to the right one, so the personal stuff stays personal and the rest runs on tokens you pay for.
Top comments (1)
I think posts like this are useful because they highlight a real gap between policy language and user experience, but the framing often leans too heavily on “bans happen randomly,” which can be misleading.
In practice, account enforcement usually comes from automated risk signals, abuse classifiers, or ToS boundary cases—not a single obvious user action. The problem is that these systems are largely opaque, so from the outside it feels arbitrary even when it isn’t.
What’s missing in most discussions is:
clear categorization of what actually triggers enforcement (content type, automation patterns, billing anomalies, etc.)
transparency on appeal outcomes (why decisions are upheld/reversed)
better user-side observability before hitting a hard ban state
So while the concern is valid, the real issue is less “getting banned for no reason” and more “lack of visibility into enforcement rules until after the fact.”
More clarity here would reduce a lot of confusion in the dev community.