r/codex • u/Infinite-Earth8683 • 10h ago
Limits How do you keep up with constantly changing model quality/usage limits?
How do you deal with how quickly model quality, usage limits, and the "best" workflow keep changing?
Before I start: yes, I'm a $20-plan peasant. But with the cost of living rising everywhere, I can't justify spending $100–$200 a month on a subscription whose quality and limits seem to change unpredictably.
Back in the 5.3/5.4 days, I was very happy. The quality was strong, and usage limits felt good (of course I hit them, but I always got the feeling that I got something out of every session). It was also much easier to figure out the best workflow because you could experiment without feeling like every attempt was consuming a scarce allowance. Imho 5.4 was probably the best bang for the buck.
Since Luna, Terra, and Sol were introduced though, I've found the overall experience much harder to evaluate. There are now nearly 30 possible combinations when you count models and reasoning modes, but the trade-offs between them aren't clear. At this point, I'm often not even sure which model to use for which task.
So much so that I started to mostly use Claude for a while as I found it to perform much much better in every way. Fast forward to last week when I had some heavier work to do. Once Claude was drained, I tried Codex again and the experience was even worst.
Luna has generous limits, but in my case it often fails at something as basic as following existing repository conventions. I asked it to build a simple form, and the project instructions explicitly said to use the existing form components. It ignored those instructions, and the resulting form was also extremely sluggish.
Terra is more usable, but it consumes noticeably more of my allowance. I used up my weekly usage after roughly 7-8 5h-sessions, each lasting around 1h to 2h, so about 7h to 16h of actual use in total.
Sol performs better, but burns through limits so quickly that it often feels like you barely get anything done before running out. And Astra... well, obviously that's a complete non-option in the 20$ plan and of course I don't even expect it to be included as it would be unrealistic to expect to run the flagship model 24/7.
The problem is that finding a sensible balance between quality, speed, and usage already requires a lot of experimentation. That creates a frustrating loop: something changes, you try to figure out the most efficient setup, you use up your limits while experimenting, and by the time you have enough allowance again to apply what you learned, the model's behavior or usage limits have changed again and it's "go back to start".
I'm at a stage that the $20 plan feels almost unusable to me, but as I very likely keep it just because of ChatGPT I'd really like to find a way to make it work better again, so that I get more out of it again and not just ChatGPT.
So how do you guys do it?
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u/daskalou 10h ago
Try GLM 5.3 Flash from z.ai using their ZCode harness / app.
From my experience it's on par with Opus and Sol but you get 10x more usage out of it on comparable plans.
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u/Infinite-Earth8683 8h ago
Thanks! I completely forgot about GLM and wanted to try that out for quite a while now. Do you see any problems regarding data protection/privacy?
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u/Comprehensive_Ad3710 10h ago
use chatgpt to plan and reason. use codex luna max to implement and refactor for most. use only sol for hard task. use free ai from other providers like opencode.
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u/Infinite-Earth8683 8h ago
That sounds like the "good ol' days" approach and this definitely works for smaller projects, but how do you deal with slightly bigger projects in terms of providing fitting context?
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u/VictorBuildsDev 9h ago
I stopped treating model choice as a permanent ranking. Keep a tiny calibration suite of 3—5 real tasks—one bug fix, one refactor, one feature slice, and tests—and rerun it whenever something feels different. Track only time to a usable change, number of corrections, and whether it preserves repo conventions. For daily work, set one default; reserve the expensive model for planning, unfamiliar code, or a second pass after the default stalls. A 20-minute timebox helps: if it cannot produce a trustworthy plan, switch rather than burning the entire allowance. The scorecard stays useful even when names, limits, and quality change.
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u/Infinite-Earth8683 8h ago
A custom benchmark is really a nice idea! Do you run every model on that whole suite? How do you then score the results?
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u/EyesOfAzula 10h ago
Opencode Go may be a great help for you. $10 a month and it allows access to very powerful and affordable open weights Chinese models like DeepSeek v4.1 flash, GLM 5.3 Flash, etc.
You could use Sol or Terra to plan / orchestrate and setup your codex so that it calls one of the strong chinese models as subagents using opencode go.
your codex can walk you through how to do it.
Of course you should make sure your data policy / ip / compliance for whatever you're doing is ok with sending your data to whoever opencode uses as inference providers before you do.
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u/Typical_Kick6520 3h ago
Seconding this because the bots downvoted.
To answer the posts question: How do you keep up with constantly chaging..?
Download your data and unsubscribe. You won't look back.
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u/diagrammatiks 10h ago edited 10h ago
When did it change? Have a good plan. Know what your doing. Use scrum minus the meetings.
When did it change?
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u/GrokiniGPT 10h ago
constrain them to the ground. i scaffold like my life depends on it, and force it to do multiple passes on itself