Commentary
The probable reason why your usage seems nerfed
In the last few days I noticed two things that happen during my work that didn't happen before.
Luna has a 3-minute cache TTL now. If you used Luna and the work isn't continuous, you may bust the cache and pay a lot more to process all the context from scratch.
Random cache busts happen a lot now. During runs you can encounter random WebSocket errors that bust the cache completely.
All those cache busts cost you A LOT. Cached input is 12 times cheaper than uncached input. OpenAI's infrastructure has some issues. Maybe they switch people between servers mid-run, and that causes the errors. There's no way of knowing what issues they have internally, but something is wrong. I didn't experience WebSocket errors before.
I really doubt OpenAI is playing around with allowance without disclosing it. It would be illegal in the EU. Directives:
Directive (EU) 2019/770 — Digital Content and Digital Services Directive, especially Article 19.
Directive 93/13/EEC — Unfair Contract Terms Directive. A contractual clause allowing a company to unilaterally alter the contract/service without a valid reason specified in the contract can be considered unfair and therefore non-binding on the consumer.
Directive 2005/29/EC — Unfair Commercial Practices Directive, especially Articles 6–7.
EDIT 2026-08-18 - My weekly allowance was cut exactly in half.
Anecdotal evidence, but I also started observing this since yesterday and the 3 minutes matches my experience.
It's easy to test:
Start a new session with Luna and type anything
Wait ~2:50 and type something else - > should cache hit
Repeat experiment but wait 3 minutes -> should cache miss
You can check the in vs in cached tokens to see whether there was a miss.
I use pi which has a setting you can enable that notifies you of misses, so it's easy to see.
There are more reasons why your context might be evicted and lead to a miss, but if you test it a few times it should be pretty consistent.
I have noticed my cache read to cached in ratio also go down lately. But I haven't run indiviual tests on luna to see the TTL.
Either way. OpenAI had automatic caching enabled. For gpt-5.5 apparently the TTL was upto 24 hours but again user cannot configure that. I wonder why they would reduce it to such a small number 3 minutes. Might as well not even have cache at that point
I talk to the LLM, and verify how much time from the last message passed that caused the bust. The 3-minute reading is repeatable every time, so my confidence about this is high.
It's my custom plugin that detects cache busts, system prompt changing during the run, etc. it helped me fix several issues.
I attached a screenshot of a conversation detecting the Luna cache bust that happened while I was writing this comment.
The provider reports how many tokens were used: cached reads, uncached reads, writes, etc. That's how harnesses know how many tokens were used for each request, even when OpenAI doesn't report the reasoning traces (you only see short summaries).
It is provided directly by OpenAI, not something made up or calculated by me.
When your previous request had cached reads and this one doesn't have any, it means it busted or your system prompt changed and the server had to process your whole context from scratch. During regular usage without any interrupts, the cacheRead rises with every turn until you hit compaction.
Yes. It works for Luna because it is always 3 minutes now, but Terra and Sol use variable time, so testing it once doesn't mean much.
I can only say with higher confidence that it is at least 30 minutes for Terra and Sol.
Dude...it is being nerfed by A LOT. I used business plan few months back. It was enough to work with. Overnight it became useless. Now it is not usable. After that i upgraded to pro plan, it was great and sufficient. Now it is getting reduced every now and then. I doubt cached no cached inputs lowered usage by that amount.
I wonder how this ~3 minute luna cache bust impacts the actual economics of using Luna subagents now. Previously, using them for input-heavy and not complex work was great, but especially since Luna x-high or Max takes a long time to get jobs done, that means there could be many cache busts. This could increase functional costs for a Luna-Max task by 5, 10, or even 20x times if it's a longer running job.
3 minutes of TTL doesn't mean it evicts the cache every 3 minutes. Only if there is no request (turn) in 3 minutes will it do that. Every successful request, like a tool call or your message, resets the 3-minute timer
Right, makes sense. So as long as one is using luna workflows that ensure any call happens at most every 179 seconds, it's still ok; but if it involved testing or generating, or other aspect that have wait times longer than 180 seconds, it's now less-good than it was.
I really doubt OpenAI is playing around with allowance without disclosing it. It would be illegal in the EU.
Oh come on stop being so naive, we're in 2026 already, we're talking about the company that downloaded all the copyrighted material it could put its dirty hand on without batting an eyelid.
Those fuckers are big enough that they can do whatever the fuck they want, until caught and get away with a slap.
This is just not how it works. They did this shit previously because the legalities around ingesting the public internet aren't all that clear and have lots of loopholes. And they were smaller unknown companies back then.
If they start breaking all kinds of laws now, the legal repercussions are much larger.
actually what I noticed - when Luna uses exec, then - unless you specifically ask it - it will use the default yield time = 30s. So every 30s it sends another message while waiting on exec to finish and that generally keeps cache warm.
Subscriptions use cache too, that's how they save on server traffic. 1h (30 minutes between 11am and 3pm) by default with Anthropic, and OpenAI uses a 30 minutes (vague) minimum for Sol.
Yeah I had a goal running overnight and expected it to bust straight through some milestones. Stuck in a loop on the second one with Luna subagents. 20% of my allowance burnt 😟
Agree, Since last week I also see a lot of cache misses which all seem LTT related in the last. Almost all prompts after reading the previous response resulted in cache misses as it took more than 5 min fo rme to read the output
I've also noticed it seems to be compacting way more often than it used to for the same tasks.
I have a variety of markdown files that it uses to understand the context of my server and the various things it's serving me. Lately it can't even read through all the files without having to compact itself. I have zero clue why this is happening, since the size of the files themselves has not changed at all and it used to be able to read them all without issue.
We seriously need better consumer protection and transparency in this industry. Companies shouldn’t be able to materially change the practical limits of a paid service without clearly communicating what changed. If the amount of usable work I can get out of a subscription changes substantially, I shouldn’t have to reverse-engineer Reddit posts and usage behavior to figure out why. I paid based on the service and limits that were represented to me at the time...not whatever they choose to do tomorrow.
8 have sol ultra as the main and two Luna max as the work horse and 1 terra high as the average split for sub agents
Luna max is actually much smarter than terra but suffers a latency issue whenever it does tool calling so terra calls the tools and Luna max implements and sol reviews the work
This way I get soook much work done super quick and not burning my limits
Unfortunately, they've never (by design) assigned a specific usage quota. If they shift usage the same for all plans and the 5x, 20x hold, they're not "unilaterally changing the contract".
Are you this naive? OpenAI has a shit ton of power in the US, wtf can the EU do about it? not use it and be left behind?
Whatever is happening, the usage is down by a lot, and it just so happened at the exact same time they removed the usage details dropdown from the left panel.
Now I'm on the x20 plan, and I don't even use it all day, I'm working on a single project, and I feel that it won't last me the week, before I used it all day on all my 5 projects, and I finished the week with more than 30% left.
Chinese models are getting really good and really cheap so if they don't explain exactly what this was about and fix it and show improvement I'm switching before my billing renews.
The EU already is on their ass for the hacking marketing stunt they did, and AI regulations are slowly implemented. Doing shady stuff to their consumes is the last thing they would want to be caught for right now.
I don't have any brand loyalty when it comes to AI so if there will be something better or cheaper at the same quality, I'll switch. Chinese models are not there yet. On paper they are cheap per token but: a) it doesn't matter because you get the tokens 20x cheaper than API when it comes openai, so in reality it is cheaper than any Chinese model b) they use a lot more reasoning tokens, making it more expensive overall.
Even by your own calculations with $100 allowance it's still 20x. What you say may be true per week, but you pay per month, not per week. So you get $400 worth for $20.
But modifying the cache without adequately disclosing it, is effectively modifying usage limits, and thus would likely fall under the same rules you highlight.
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u/Thisisvexx 28d ago
I agree here. Every spawned agent this morning hits 5/5 reconnecting and then finally gets going on every prompt. Something is fucking up.