I am finding that I am now less interested in better models than I am in token budgets. My issue with Anthropic models now is that I don't feel like I can rely on them as a daily driver because they'll dry up before my quota resets.
I am becoming dependent on AI to make a living, and I need predictable spend on it. If I know I can't use a model regularly all month, my enthusiasm is limited.
I urge Anthropic to get better at this aspect of their business so I can come back to it.
Invest a bit of your time into optimising usage cost. Anthropic has first class docs, actually read it or ask llm to read them all for you and summarise most important points / ask to to reflect it on your .md files. Maybe silly thing like dropping your default thinking effort by one level or adding (sub)agent pinned to other model is all there it to completely fix it or maybe you have instructions that encourage big dumps in CLAUDE.md/AGENTS.md that needs splitting so progressive disclosure works correctly? Naively sending everything to the most expensive model on high thinking effort is anti pattern and will drain quota quickly.
My personal guess is that it's one of those. With effective context engineering it's hard to use all 20x quota, the limit becomes your own attention and time really.
I literally only make it halfway through the week until my weekly usage runs out. This is using only Opus, no fable, and I'm on the max x20 plan. It's become ridiculous.
These comparisons are meaningless
I use Opus every day and easily have most of my weekly limit left over at the end of the week
just buy two 20x, no?
or switch to codex
Agreed. The area I think will become more prevalent in the future for organizations are cost per intelligence -- effectively efficiency. An unoptimized model that costs 90x more than another that is only 10-15% less intelligent is something I would say is not a good deal.
I am on the Claude Max 20x plan, and this still happens when using Fable 5/Opus 5. I would run out of weekly quota in 2 days, whereas Opus 4.8 would last the entire week, and sit at about 80-90% at the end.
GLM 5.3-flash fits the bill
What is it equivalent to?
What kind of things are you using it for?
I haven't tested it yet but on all the benchmarks it looks like it's 5-7x slower for agentic tasks.
I made some webapps with it, and have it running my hermes agent (which also does a lot of coding, but not webapps).
Not sure what it's equivalent to, but it's super cheap and I am happy with the results
It's a mix of slightly worse kimi k3 for UI work and slightly smarter than luna for everything else.
But yeah, it's very slow. I've put it to work as an LLM-as-RAG agent.
I'm with you, for what I usually do most models are already more than enough.
What I'm really keen on is better auto-reasoning so I don't have to constantly have the constant inner debate on which reasoning effort to pick for each task.
I seriously hate the none-low-medium-high-xhigh-max-ultra etc that we have now, with companies frequently recommending different ones on each new model release, etc.
It's apparently called Adaptive Test-Time Compute or Dynamic Test-Time Compute and companies are apparently working on it (according to some LLM :shrug:)
Adaptive reasoning is known to be an extremely hard problem to solve, though. It requires you to predict whether a certain LLM, with a certain effort level, with a certain prompt, will give you the right answer.
Try gpt 5.6 Luna max
Have you tried Grok 4.6, if you're focused on token budgets? In a league of it's own for tokens/intelligence.
Not for enterprise. Can't trust the company behind it with my data.
SuperGrok quota is garbage for anything coding. I burn through my quota in a few hours with very mild use.
SuperGrok Plus is slightly better but doesn’t last me more than a few days. Even Claude Max feels leagues more generous in usage…
I haven’t tried SuperGrok Heavy because it’s too expensive
All of the subscription AI platforms are trimming down quotas across the board to push users into higher tiers. Whatever they can do. Local inference needs to meet pricing sooner