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If you are paying for a plan and GPT-6 Astra is not in your model picker, nothing is broken. Access was staged from the start, and the staging is the reason — not your account, your region or your browser.
Staged access and an outage look identical from the user's side — the model is not there. They need completely different responses, so establish which one you are looking at before you start debugging.
If you were planning to build on Astra specifically, the sensible move is to write against a model you can actually call today and keep the provider swappable. Pricing at this tier is close enough between providers that the switch is rarely the hard part.
Nothing in this post is Runyard arithmetic — these are reported figures from launch coverage. Where we compute things, we say so and you can check the working. Here we are relaying.
The pattern is consistent enough across launches to plan around, even though no provider commits to it publicly:
If you are not in the first two groups, the fix is patience rather than troubleshooting — and knowing that saves an evening of clearing caches.
The practical lesson from every staged launch is to keep the provider swappable. At this tier the pricing between frontier models is close enough that the switch is rarely the hard part, and being able to fall back to a model you can call today is worth more than being first onto one you cannot.
At the margins, yes — higher tiers are usually earlier in the order. It is not a queue you can buy your way to the front of within a tier.
They roll out separately and often in different orders. Seeing a model in one surface says nothing about the other.
Yes, and it is common for new capabilities with regulatory implications. If colleagues elsewhere have it and you do not, that is a plausible explanation and nothing you can fix.
Usually a partial rollout being pulled back, which is normal during a staged launch. It is not your account.
What a frontier-priced API costs against running something locally.
Compare the real costs →Tools
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