YHK - yet another hacker news clone

Does anyone care about code quality anymore?

Should be B vs A correct?

Else it's confusing

Its a great release, I will use both heavily.

https://developers.openai.com/api/docs/pricing?latest-pricin...

This is great, but practically, I'm not going to start working on more side projects.

Perhaps in another 6-12 months I'll be fine to drop down to $20/m instead of $200.

>> $4 → $2

>> $20 → $10

Do you mean 100% more expensive? GPT 6 is 100% more expensive than 5.6 per your post.

If these price changes mean that coding plans have effectively more usage then that's great, but Codex is surviving on resets from my own experience using it. I was glad to go back to Claude.

The parent + subagent workflow has become critical for keeping the reasoning agent (parent) context-lean while also letting me chat to the main agent while work is getting done.

My main process is to use Fable to reason and then spawn Opus subagents, and I get amazing results, and I'm always looking into what the subagents are doing.

Did cache read/write also decrease by 50% or similar? That's where most (95%+) of the cost is for agentic coding workloads.

Asking cuz I don't think I'm a bot [pats self], I legitimately prefer the GPT models to Anthropic's, don't like Anthropic's customer service/reliability story at all, and I welcome a massive price reduction. Seems like something I should be happy to get.

If you'd told me I'd be typing this a year ago I'd be skeptical though.

Highlight and lowlight of my week was successfully convincing the OpenAI support chat robot to give me a refund for the month for my issues with 6 chewing threw my usage with no output.

Terra ended up just being an awkward middle ground that was not particularly suited for any workload.

Funny thing is they very recently also set a real limit per-user/month, so why even limit the models because theyre "too expensive".

I was hoping for a serious Luna upgrade. It was already cheap enough. This feels more like a price reduction than an upgrade.

That said, if the new Luna is able to handle ultra mode and subagents v2 in codex cli, then at least that’s a win.

fyi, i flagged it because it is boring reading and against the rules.

if you suspect astroturfing, flag the comments and contact the mods.

(complaining that your complaint got flagged is also tiresome. contact the mods. "@dang" doesnt work, use the email.)

On the other hand, you have previously written: I'll gladly admit I think what these companies are doing is unethical, and I'm sure that biases my thinking toward skepticism. [1]

You have now posted accusations/assumptions of astroturfing and manipulation at least 15 times, without ever providing any evidence. This is in breach of the guidelines, because comments like this poison discussions far more than the comments they're complaining about.

We – of course – want all comments and posts on HN to be authentic. HN is only a place where anyone wants to participate because since the beginning, we've had software mechanisms and moderation practices that detect and weed out inauthentic commenting and voting. We're identifying and dealing with it every day, continually improving the software to detect and remove it. Most of that happens quietly and efficiently in the background without anyone having to see it. When users see evidence of manipulation and report it to us via email, we happily and thoroughly investigate it.

Most of the time, what we find is simply that people are authentically excited and passionate about the topic, which is what is happening here. I understand it can be hard to accept that if you're skeptical about the topic.

It's fine to be skeptical about the topic and you're welcome to express your skeptical views on the topic. People do that every day on HN, about AI-related topics and countless others. Healthy debate is what we're here for.

But you can't keep poisoning HN, by (1) continually posting these unfounded claims, then (2) when users and moderators simply uphold the guidelines, staging a protest by demanding your account be deleted. This is not what people do when they care about a forum's health.

[1] https://news.ycombinator.com/item?id=48220908

As far as I know Codex (at least the GUI) can automatically call the ChatGPT Chat models (including Astra 6 Pro), you just need to @ a ChatGPT Chat conversation from within Codex and tell it when to use it.

> There used to be a toml file workaround for Codex to extend the GPT context window to 1m, but this stopped working on the plans and only on per-token billing

Not true, it works again[1]. I confirm that it works both on 5.6 Sol and Astra 6, possibly other models too.

[1] https://x.com/thsottiaux/status/2089082893804896524

Having limitless webUI ChatGPT usage is much better user experience, though. I'll give them that.

(edit: Sol-6 is half the price, so maybe the usage limits are going to be way better.)

Opposite in my experience. I need to limit codex to 500k on medium/low, still run out in 2-3 days with 1 CLI window. CC gives me 4-5 medium/high days with 2-3 CLI windows, and Opus is still great for other regular dumb engineering/refactoring.

On the other hand my head starts to hurt if I read Opus for too long, hopefully they fixed it with 5.5.

This hasn't been the case since around July. If you measure usage in raw api costs, Anthropic is actually giving more on $200 than OpenAI now. This includes resets. Usage allocation difference would be humiliating for codex subs were it not for resets. But fixing usage limits with resets is ugly, and they're not good for your mental well-being.

> Context window in the harness

Codex now allows 1M for subs with config params. But generally speaking, you shouldn't really be using 1M context. If you accidentally send a request with say, ~700k context already accumulated in a session which is outside cache TTL, you're paying full cost of these 700k tokens.

> I've subscription hopped a bunch

OpenAI actually has a new strategy to prevent subscription hopping after their 2-3 month-long marketing push to get claude-folks to switch over:

you can't buy a $200 sub anymore. So if you cancel, you won't be able to get back in. Hostage situation, essentially.

EDIT: re: usage limits, oh-my-pi maintainer has been tracking this - https://nitter.xitter.cc/_can1357/status/2090075496948060372

Compare that to Claude and I can run multiple agents on Opus almost indefinitely. YMMV of course but I was shocked at how quickly I burned through Codex usage.

On the context window, I feel so cramped on Codex, compacting happening every time I turn around is annoying. I didn't realize how much I enjoyed the Claude context window size.

That isn't a valid comparison, since Codex 20x is closed. So we should be comparing Claud 20x to Codex 5x + credits.

Also in Codex, even though you can increase the context window to 1m so its on par with Claude, exceeding the default is billed at 2x.

While you're understandably not including the values of the $20 standard plans on both, I find the generosity of then token limits on ChatGPT plus vs Claude Pro (it's a huge difference) to be good representation of their respective attitudes towards the average user. You literally cannot use Claude pro to build real software, unless you're extremely frugal with your prompts and don't try anything even a little ambitious.

Also, Anthropic has zero models comparable to Luna.

I'm quite puzzled about why Anthropic is so hellbent on blocking other coding agent. It's not like Claude Code has any secret sauce, right? And does Anthropic make monkey off API usage, and their magic is on the model side anyway?

The GPT / Codex models have always been "overengineer" personalities. I prefer that to "I left a pile of race conditions lying around and big gaps in testing" though, which is what I was getting from Opus at times.

But yes both Astra and Sol veer on the side of paranoid. And honestly that's better for team work. For solo work where you just want to yeet something, it can be tiring.

You learn to tame the GPT "personality" on this front by combing over once a week and asking it to find and exterminate pointless tests, clean abstractions etc.

Is it? It was already too cheap to meter for me. Luna 6 is actually worse on some benchmarks than 5.6. I’d have loved improved performance for 2x the price than ~equal performance for 0.5x the price.

> GPT‑6 Luna vs. GPT‑5.6 Luna | $0.20 → $0.10 | $1.20 → $0.50 | 50% cheaper

I can read it as follows (below), meaning that GPT-5.6 is 50% cheaper.

- GPT-6 = $0.20

- GPT-5.6 = $0.10

I'm so tired of looking at benchmarks. I always look fwd to the pelicans.

But effort is basically how much extra internal scratchpad to use and how much extra questions to ask and answer before producing a result, Exploring more hypotheses, validating consistencies, calling more tools.

If you’re happy with your token spend on Astra then keep doing what you’re doing. but if you feel the need to conserve tokens, then you can do that by switching to smaller models like Luna when the task is straight forward.

If you have something that needs to be done right, might be a bit complicated, up the model size.

You can see this in the pelicans. Big model pelicans are pretty accurate by default. Up the reasoning and only more so, but with more detail. For Astra, it is 105 lines for low, 250 lines for max reasoning.

Small model pelicans will lack the fidelity of a large model. Bits will be out of place etc. For luna, it's 90 lines for low, 150 lines for xhigh.

Additionally the amount of time taken is increased for the larger models. Luna takes 11 seconds on low, and 1:33 for xhigh. Astra is 33 seconds on low, 4 minutes on max.

And naturally, there is the cost. There's some overlap in functionality between luna xhigh and Astra low in the sense that luna really can do quite a suitable job for some tasks. But there are just some tasks that just don't make sense for Luna, even at high reasoning.

The other thing to remember is that sometimes high fidelity isn't ideal. It can lead to overdesigning. My recommendation is to commit early, commit often, and review everything you do, which we've all been doing since before LLMs right?