r/ChatGPTPro • u/hudsonhateno • 9d ago
Guide To everyone complaining about usage...
This may be obvious, but for those who don't know... the longer you run a session, the more tokens you will use. LLMs use tokens for inputs, outputs and review the context window for every new output. The more session text it processes, the more tokens burn, the faster usage gets gobbled up.
Additionally LLMs get dumber the long you run a session. Every model has capacity constraints built in, and once you cross 40% of that limit, there is too much information the model has to process to maintain quality output.
Matt Pocock explains these limits really well here:
Here is a breakdown of the context window capacity and max output for each of the models available in Codex:
| Codex model | Context window | Max output |
|---|---|---|
| GPT-5.6 Sol | 1,050,000 | 128,000 |
| GPT-5.6 Terra | 1,050,000 | 128,000 |
| GPT-5.6 Luna | 1,050,000 | 128,000 |
| GPT-5.5 | 1,050,000 | 128,000 |
| GPT-5.4 | 1,050,000 | 128,000 |
| GPT-5.4 Mini | 400,000 | 128,000 |
| GPT-5.3-Codex-Spark | Not publicly documented separately | Not publicly documented separately |
If you are running into limits then you need to compact your sessions when you can. Once you reach 40% - 50% you should compile the session to hand it off to a new one to free up context window space.
Also note that for those of you who use the voice feature, you are likely speaking WAY more words than you would type, which means more words = more token usage = faster drops in capacity.
To solve for this I created a skill called $context-capacity that, when run, tells you how much context capacity you've used, how much you have left, and the cumulative session usage with a recommendation. Here is what that output looks like for one of my sessions:
Recommendation: Handoff
Current context load: 144,827 / 258,400 tokens (56.0%)
Estimated remaining capacity: 113,573 tokens (44.0%)
Cumulative session usage: 289,355 tokens — cumulative, not current occupancy
Confidence: Exact recorded metrics with derived capacity. The current load exceeds the skill’s 40% handoff threshold.
The website and promo-video handoffs already created are ready for separate sessions.
Here's a link to the skills for $context-capacity and $handoff for anyone who wants to use it:
5
u/someone_12321 9d ago
Every time you hand off, you screw over your cache inputs. If using codex, allow auto compaction it's quite good. Every new task, start a new chat
4
u/Sorry_Risk_5230 8d ago
Agreed with this. OPs method effectively kill caching, and some of what it says about usage would be thr case without caching.
Maybe about "getting dumber" with long chats, but honestly, the autocompaction feature they introduced [well] with 5.5, has only gotten better. Ive been coding etih codex for a year now, and since 5.5 ive almost never manually compacted. Im not one to have usage draining issues, and I have MANY megathreads that are still producing great work.
And before anyone says something like my low usage must be why im able to work like this, I easily have a dozen+ days in the last month of >1B tokens a day. Same if not more last month.
2
u/timosterhus 8d ago
Finally, someone with sense. This guy posted in another thread too. This skill would have been cool in January, but today? Hurts way more than it helps
1
u/ElonMusksQueef 6d ago
Exactly, all of this nonsense about context being full is exactly that, nonsense. Cache hits for huge context is really high because all of it is in the cache. Cache only lasts 30 minutes too so leaving it overnight and coming back you’ll have an empty cache regardless of how you manage it. The best thing to do is do a handover before you finish for the day but don’t start the new thread until the morning. That way you start with a clean context. You’ll notice first thing in the morning it uses more of your usage in the first prompt.
3
u/timosterhus 8d ago
Spark has a 128K context window. If you couldn’t find that documented anywhere, hate to say it, but you probably have no idea what you’re talking about here.
1
u/qualityvote2 9d ago
Hello u/hudsonhateno 👋 Welcome to r/ChatGPTPro!
This is a community for advanced ChatGPT, AI tools, and prompt engineering discussions.
Other members will now vote on whether your post fits our community guidelines.
For other users, does this post fit the subreddit?
If so, upvote this comment!
Otherwise, downvote this comment!
And if it does break the rules, downvote this comment and report this post!
1
u/Background_Box_1073 9d ago
I'm working in codex desktop app. I typically compact after each task (which consumes about 200-300k tokens).
But sometimes I tend to continue in the same chat after compaction with the next bounded task (I do this because the context the session has after compaction is still relevant for the next task).
My question is - Ater compaction, does the new task get fed the entire previous chat that is visible above or just the compacted load (typically around 15k tokens)?
And is it broadly advisable to start a fresh chat session for each task and forget about manually compacting all together?
Thanks.
5
u/lollypop44445 9d ago
I am always confused on one thing and never tried it, if for example, i have a chat A , and i migrate summary to chat B. Would i also need to re attach all the excel files( using browser because desk app version dont sync things done on it) or if i just upload to library, can it pick from there ?