Posted by EugeneOZ 5 hours ago
There are huge token efficiency/bloat differences between agents while working on the same tasks, using the same model, in the same environment
Yesterday I ran 10 agentic tasks using GPT 5.6 Sol in an ubuntu 26.04 vm a couple of times with different harnesses and got vastly different token usage.
+-------------+-----------+-----------+-----------+-----------+--------+
| Harness | API total | Input | Cached | Uncached | Output |
+-------------+-----------+-----------+-----------+-----------+--------+
| smol | 172,807 | 142,334 | 8,704 | 133,630 | 30,473 |
| Pi | 427,211 | 392,767 | 137,216 | 255,551 | 34,444 |
| OpenCode | 1,564,429 | 1,523,957 | 1,204,736 | 319,221 | 40,472 |
| Codex | 3,005,744 | 2,953,154 | 2,649,344 | 303,810 | 52,590 |
| Hermes | 3,856,611 | 3,808,231 | 3,167,232 | 640,999 | 48,380 |
| Claude Code | 5,073,137 | 5,029,969 | 4,587,008 | 442,961 | 43,168 |
+-------------+-----------+-----------+-----------+-----------+--------+
https://x.com/__tosh/status/2083593799872237680I'm not surprised that Claude Code is not optimized for an OpenAI model but I was still quite shocked re how much of a difference the harness makes.
Disclaimer: I'm working on 'smol' which is a minimalist harness but it's really nothing special, just a minimal system prompt, no skills files, only tool is shell
Do not underestimate how much popular harnesses are spamming the context window. The context window is very important.
The difference in tokens between the two also makes super curious. The system prompt can't be that different (I'd even bet Pi's shorter) and the 4 tools shouldn't make as much of a difference. I'm gonna have to try it.
It is everything. My experience with Claude Code is that you have to decide when to compact to make it efficient. It defaults everything to 1M context and it will never keep it in check. It is strange how little cache reads you hit in smol, that may be a configuration issue.
Do we have any insight into whether it is actually spam and not useful info such as project or programming language specific context?
You should use --disallowed-tools to prune any tools not needed for the task. Note that this is also a perpetual game of whack-a-mole since they’re always adding new tools.
It's so unfortunate they don't let you use the subscription with other harnesses anymore - since even if I used OpenCode they'd still get a bunch of useful data from the API calls, meanwhile I could stretch their tier limits way further.
Your subscription is not subsidised, it is just closer to the actual cost of the model…
200$/month is a lot of money on Luna/DS4 flash, like really a lot and the results are much better than clowning on bloated CC.
It's absurd how you have more and more organizations encoding their processes on LLMs and "engineers" (charlatan coders) don't even bother optimizing the tool they use most.
I won't argue with the cost effectiveness, but the results are very much not better. Opus and Fable are in a different league than DS4 Flash. Even GPT Terra, which I really like overall, sometimes gets stuck in weird loops and starts to do stupid stuff once its context window fills up. Whereas I can more or less trust the big models to just Do The Thing™ on the first try.
With that said, you get way more value out of a GPT subscription than you do from Claude, partly because of the ability to use more efficient harnesses.
I’m not sure if they let you skip the cache write cost on the first turn. That would imply cross-user caching infrastructure or special casing the default system prompt to give you a discount. Maybe? Away from the computer but you could try a “hello” in a fresh session and see what was billed.
for coding agents 'shell' is often all you need (just make sure the environment has the necessary tools)
I’m asking because I’ve been looking for agent harness comparison tools too. I’m interested in more than just the inputs and outputs—I also want the system prompts, traces, and tool calls. It’s useful to understand why Codex, for example, uses more tokens while Pi doesn’t.
Fewer tokens aren’t necessarily better if the agent skipped important checks. On the other hand, using more tokens could just mean it’s overthinking the process. Either way, seeing the full execution trace for the same task is really valuable.
I agree fewer tokens is not necessarily better but a bit counter-intuitively often the harness using fewer tokens is not only done faster but has better results
(that said: of course check the results, look at the full traces, agree!)
the uncached tokens are also from runs where smol finished a task below 1024 tokens (the minimum amount of tokens needed to activate caching) which is less tokens than other harnesses are using for their system prompt (!)
> GPT-5.6 and later models: Caching is available for prefixes containing at least 1,024 tokens. This is a strict minimum.
https://developers.openai.com/api/docs/guides/prompt-caching
so in this specific case the count of uncached tokens for smol makes it look worse than it actually is
that said: it does makes sense to add more tasks that are difficult enough to fill the context window to compare the harnesses for how well they deal with compaction
staying below compaction (or with compaction at fewer compactions) is not only cheaper and faster, it also helps the agent stay on track
also, are you using a tool to collect those metrics? what is it?
https://news.ycombinator.com/item?id=49006862
I'll have more about it in the next hours/days, you can follow me on twitter in the meantime (https://x.com/__tosh)
Be careful here. Remember these are non-deterministic models at the end of the day, and even with everything being "the same" you can have two runs where the same model, same harness, same tools can arrive at the same conclusion through a wildly different sequence of events.
the "spamming" is mostly compaction appending files, tool artifacts, images in its summary there is a known github issue for codex. only solution is periodic clean up but its also how a lot of the agentic orchestration is performed and able to work for days.
like creating a checksum of a file, merging csvs and so on, fixing a makefile pipeline
with known 'good' outcomes
all harnesses could reach the outcomes, only cost, time, number of tool uses and so on were different
(Claude Code failed once in 1 task but I think that was just an unfortunate outlier, the tasks aren't that difficult)
These days I “write” code with claude code and codex, and read/review it on GitHub. If I need to read it locally, I use a plain text editor.
Can someone help me understand what value cursor offers in 2026?
Damn, and I thought Anthropic was fast.
1) It's still an IDE. Because of pricing I mostly use Codex, but I always have a VSCode/Cursor IDE open, thus have to juggle between the two. Working directly in the IDE is more comfortable. For full on vibecoding that might be worse, but when you want to do a deep review of the changes, an IDE is way better than reading a diff on github.
2) It supports every model. It's often very helpful to try different models when you don't like the result of the first.
These days I've switched to Zed, which is good enough (and wicked fast), but I still miss Cursor as an IDE.
The $20 price point is just too competitive now and I'd rather use the Claude/Codex plugin over Cursor's agentic coding sidebar.
To answer your question though, to me your workflow seems cumbersome. Cursor is more integrated and more frictionless.
In agent mode it’s horrible for editing files etc but better if you are juggling multiple chats
Should the AI sidebar be on the left, or on the right? At some point they swapped them automatically, which was jarring (maybe a bug). But now I realize that if I'm not the one primarily writing code and navigating it, then I prefer agents in the "primary" position on the left (esp. if I have the browser on the left half of the screen, the agents are in the middle).
What annoys me the most about Cursor is the random stuff that breaks (due to its nature of VS Code fork).
The tab experience is still unparalleled. The cost might be worse than Codex/Claude sub, but they are all much, much, much cheaper than API pricing, so depends on your POV.
Especially if you are doing "remote" development through SSH. If you are doing stuff where you still have to write some parts of the code manually or you have to fix few things here and there that the AI outputs, you still need a real editor.
Unless by "text editor" you mean Neovim or Emacs ?
Diffing through a web interface offered by GitHub or Bitbucket is such a narrow window into changes.
The potential benefit of Cursor CLI (vs CC and Codex) is that you can easily between all major models (by Anthropic, OpenAI, xAI, as well as Kimi K3 and GLM 5.2). I found it useful when reviewing work - e.g. I implement using Opus then review using Sol, etc. Models by different providers tend to have different perspective on things and they can find different issues with the code.
You can still see what you’re billed on the Spending page. We did accidentally break dollar costs in the Usage CSV export yesterday while cleaning up an old feature flag. That was not intentional and the CSV export is fixed now.
That feature flag also showed a dollar usage graph to some self-serve users. The confusing part was included plan usage shown as $, which is not what you’re billed (on-demand usage is). Some people read it as actual spend, so we decided to remove that graph.
No, you can not: https://www.pasteboard.co/dNXUdT-h8Giy.png
If you want to say that "admin can" - it doesn't matter, I'm not going to ping admin every day to check how it goes. I'm not going to ask admin about every session to check how cost efficient a model was.
Double-edged sword. It is also simple to move back to VS code and agent extensions.
Gotta justify a $60B purchase of an IDE and (at the time) a single, decent model.
I imagine she’s just weighed all the details and options in her mind and plans to french fry tokens from my plate instead of getting her own.
And I hate that. I mean, I love her. She’s definitely value-add. But those are my tokens, right? My brain doesn’t do books. I can’t sit on the beach and read. I must always be swimming somewhere meaningful. So I’ll be vibing the next great Canadian web app and she’ll just casually ask, “hey what do you want to do about dinner?” So now I’m asking Copilot to tell me what I want for dinner. And it’s just… c’mon lady get your own tokens.
These days I'm using Codex and Claude Desktop with Zen when I need to look at code. Codex's real time audio chat feature (not dictation) is also second to none when paired with their agentic flow.