Looking at this, AI still has a long way to go. In Sol Max, the pelican's legs are missing on one side—how can one side have two pedals and two legs...
> GPT-6 Luna being half the price of GPT-5.6 Luna is a really big deal.
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.
6-luna is at the pareto for most of the tasks! I dont know how they make money here but its insane value from a closed source model. I'd go further and say it makes no sense (privacy, sovereignty etc aside) to use many other models as its not only expensive but also many providers don't have that much GPUs to serve at a significant volume. https://openrouter.ai/rankings?view=month#top-models 5.6 luna is already the most used model this month.
Gemini 3.8 Flash looks like its better than v7 Luna/Sol on DeepSWE v1.1 while at $0.75 per million input tokens and $3.75 per million output tokens. Luna is much cheaper, but Flash has nearly Astra's performance for under the price of Sol ($2/$10).
Yeah, it's interesting how much worse they are than the Astra pelicans. I think that reflects a tiny bit of genuine value still left in the benchmark, to be honest.
When the Astra one was last time run? It's probably better to run these 2-4 weeks after release when models get nerfed to get idea of performance closer to what it is.
Do you have a page showing all the pelicans you've ever created? Could be fun to browse - kinda like https://progress.openai.com/ but visual. (It's a shame they don't keep it updated)
I'm so tired of looking at benchmarks. I always look fwd to the pelicans.
I find it very interesting that for both these models we such a clear progression of better images with higher thinking levels from 'hardly useful' to 'pretty nice'. I feel on many other models low and max are much closer.
At this point, the deciding factors for me between Claude Code 20x and Codex Pro 20x are:
1/ Usage limits: downstream of input/output cost, but resets and obscure windows and odd 20x plan / 5x plan != 4x usage math throw a wrench into it. Winner right now is Codex by a mile, especially when you factor in ChatGPT usage (even 6 Astra Pro) is essentially unmetered on the 20x plan. Always a bummer when asking if I should see a doctor about a rash means I can't code as much. It's also is a godsend if you use an MCP like oracle to automate the process of calling the Pro model on particularly tough problems, giving better planning results or deeper code analysis without burning usage.
2/ Context window in the harness. Claude Code wins on this. 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 (ETA: noname120 pointed out this is no longer the case and it can be enabled again [1]). 252k is just not enough. Codex's compaction is very good, fwiw, but it happens so frequently that even a model as powerful as Astra sometimes loses the plot on long-running tasks.
3/ Ability to use the plan outside of the official harness. Codex wins. Anthropic does shit like bills requests as extra usage if it sees a hermes.md in a commit.
I've subscription hopped a bunch, and at times I've had both, but I keep coming back to Codex because it wins on 2/3.
ETA: apparently I haven't been Keeping Up With the Altmans and new 20x signups have been disabled for a few weeks. I am grandfathered in, which makes the comparison above pretty much moot.
I dunno about Codex-the-application itself, but you can definitely use e.g. Pi with the larger context windows with a Codex login. It puts a pretty large multiplier on credit usage, however.
I've been doing this, my only experience with codex was brutal usage wise and i just retreated back to pi pretty quickly so the credit usage i'm receiving is kinda all im familiar with. Surely seems like less than CC, but i guess not using codex makes my experience kinda not valid for comparing usage.
And ya i can go over that 240k limit, I still very seldom do, and try to treat it as the actual limit. I'm surprised to see so many people still talking about compaction to complete long running tasks, i think the bulk of the work should be somewhat frontloaded into a plan that is split off into subplans, then you can kinda open up a few options, one session with subagents for the subplans of the main plan, or just handoff prompts about progress against the main plan/relevant subplan. I just never trust the blackbox that is compaction, I feel its a recipe for disaster/context poison.
> It's also is a godsend if you use an MCP like oracle to automate the process of calling the Pro model on particularly tough problems
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.
I actually haven't played with the GUI. I probably should now that the Linux version is in beta. My situation is kind of the reverse: I like using oracle to basically zip up my repo, ask GPT Pro to propose some sort of design or refactor based on the code, then provide a step by step implementation plan for a cheaper model to implement directly in a harness on my machine. It often takes upwards of 90 minutes to come up with something but I've never been disappointed by the results. I suppose I could do this and then save a step by referencing the oracle-created thread with the @ you mentioned
And re: the toml workaround, AWESOME! I appreciate you pointing these two things out, this is my highest-ROI HN comment thus far.
I've been using Claude Pro and recently gave Codex a try again. Both on the $20 plans. I get so much more usage with Claude. It's night and day for me. Codex runs out constantly, whereas Claude I hit limits very rarely.
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 is my experience. After months of hearing how Codex limits were way higher I bumped to the $100/mo plan after hitting my limits a day early on Claude due to some heavy usage + Fable (not normal for me, I often fit nicely in the $200/mo plan). I hit the usage limit in a day with a single agent running on codex and the tiny context window was stifling. Yes, I'm comparing a $100 to a $200 plan but I extrapolated the usage (4x'd it) and it still wasn't close, I got way more done with Opus.
Using Agentsview (which might have it's own issues) I was getting ~$200 of API usage in my 1 week Codex window (paid $100) vs ~$5,000 of API usage in 1 week for Claude (paid $200).
What are you talking about? ChatGPT unmetered? No way! That was 2 months ago perhaps and it’s possible your account still hasn’t gotten the new limits. I noticed around 1 month ago I was still going full throttle on my codex subscription and my limits were barely budging, and then all of sudden people around me started to complain about limits. I thought they’re crazy, but then my account go the hammer, and that was it. If I have the same pattern of usage like I did before, basically having an agent working continuously on a coding take, my weekly limit goes in 2 days.
Interesting, rolling out new limits would explain a lot. Where did you hear this? I wonder if they detect users with multiple accounts and do that first.
On usage in ChatGPT settings, I see:
Plan limits
Shared across Codex, Work, Workspace Agents, and ChatGPT for Excel. Chat conversations are not included.
Is this not the default anymore? I am on the (now closed) 20x plan.
Not that I disagree that Codex wins out, but the deciding factor actually is - Codex Pro 20x is not available for purchase, indefinitely. So, what's the point of this discussion? People who already have the 20x sub are unlikely to cancel, and the rest of us can't access it.
theres a popular thread on claudecode or claudai subreddit that proves 20x isnt really 20x. apparently its a marketing gimmick and the recommended solution is two 5x plans > 20x at greater than half the cost of the 20x
> Usage limits [...] Winner right now is Codex by a mile
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.
I’ve been a Claude user, switched to Codex expecting usage limits to be more loose but I can’t even get through a basic sysadmin task on the $20 plan using Sol medium before I hit the 5hr one.
I think I’m gonna move back to a Claude plan. I could barely hit the $200 limit if I went non-stop on programming tasks.
Maybe it's due to 20x / 5x != 4 but I have the $200/mo Claude and $100/mo Codex and I get _way_ less usage on Codex, well under 1/4th the usage. In 1-2 days of semi-heavy _single_ agent usage with Sol High I can burn through my whole week of Codex. Again, this is not running multiple agents, just 1 at a time.
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.
Also, OpenAI is just a company I'd rather support than Anthropic.
While you're understandably not including the values of the $20 standard plans on both, I find the generosity of then token limits on ChatGPT plus vs Claude Pro (it's a huge difference) to be good representation of their respective attitudes towards the average user. You literally cannot use Claude pro to build real software, unless you're extremely frugal with your prompts and don't try anything even a little ambitious.
Also, Anthropic has zero models comparable to Luna.
Astra planner/designer with Sol+Luna subagents has worked well for me to improve context continuity. Luna generates code, Sol reviews code and runs/monitors integration/E2E tests. It's about 20% more usage efficient and 20% faster to finish tasks. I've been very subagent-skeptic for a while but the economics of codegen with Luna have made it click. This just works in Codex with a single-line AGENTS.md instruction.
> Ability to use the plan outside of the official harness. Codex wins. Anthropic does shit like bills requests as extra usage if it sees a hermes.md in a commit.
I'm quite puzzled about why Anthropic is so hellbent on blocking other coding agent. It's not like Claude Code has any secret sauce, right? And does Anthropic make monkey off API usage, and their magic is on the model side anyway?
Usage is actually Claude now because of Opus 5.5 since it a better model that Astra. I maxed out my 200$ Claude plan with 10b token on Opus 5 and 5.5 is cheaper. I maxed out two Codex accounts with like not even 5b tokens.
I've been working with agents all year, but 5.6 Sol was some sort of sweet spot for me. Something about how it communicated verbally and its engineering instincts just clicked for me, and I was able to somehow predict it and jam with it. Like a colleague you click with. It's the first model I've gotten attached to. I'm concerned that whatever model supercedes it, while technically better, just won't feel quite as natural to work with. And this makes me feel very professionally vulnerable to the labs. I miss the days when my crucial tooling came from companies as reliable and predictable as, say, Jetbrains.
Astra was/is superior for planning type tasks. It was capable of doing seemingly magic things with rather vague/lazy instructions ("I need to be able to test this on Windows, maybe a qemu VM or something? Shrug." ... 1 hour later "yeah i built you a whole qemu + eval windows image + harness of powershell scripts + shell scripts to retrieve & verify harness.").
And for UI work -- which is not something I do a lot of but do here and there -- it was clearly superior to 5.6 Sol.
But it also feels sloppier? Somehow. And too expensive to use.
I felt this way with Sol in the 5.6 series and was one of the seemingly few people on this earth who liked Terra for that reason. I would often have a very specific code-manipulation ask, e.g. "add a parameter to this method, ensure all callers pass it in, if there is not a logical way to derive the parameter to be passed in a particular instance, flag this in your final response", and Sol would go on some rabbit hole side quest to refactor my codebase to determine some way to derive it rather than flagging it as I had asked.
Terra had the "workhorse" quality where it could do these changes in bulk and follow directions without being too 'smart' (but sloppy) as you described. Luna was a bit too dumb and would make sloppy mistakes; I see that more as a "run these tests and format the results" sort of model. Maybe 6 Luna will be better.
I also just reread your comment and realized the naming convention is still extremely confusing with respect to ordering of [Family]x[Model]x[Number].
Glad you pointed out the UI work. I've been doing a lot of it and it's so much better than 5.6 as UI, it's unbelievable. I give it super ambiguous instructions and it's reading my mind. I do the same thing with 5.6 and I'm correcting it for a few minutes.
Completely agree. I've been using 5.6 still even with Astra available to me for most tasks. It's funny how much of this is just "vibes" because I cannot quantify what it is. Astra is definitely better when I have an ambitious feature, but in like 9/10 tasks I prefer working with 5.6 Sol. A few weeks ago when the limits were seemingly higher, having 5.6 on fast mode was a good time.
This has been my experience for a year. Same with Opus models. This is how I think this tech will be best used in the long term - finding the one you vibe with most. Much like IDEs!
Not only was 6 worse the 5.6 Sol for my me, but it went through my Plus usage in minutes, while I could cruise for hours with 5.6. It would churn on a basic prompt for minutes and then just give up on usage limits.
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.
I had this experience as well, but after rewriting my agent instructions it has been far better. I believe Astra’s “token efficiency” translates to “don’t research as much” which caused it to make poorly informed architectural decisions.
Similar for me. gpt-5.6-sol high has been my go-to for months. One of the reasons I'm pushing myself to try open models more is because it lends some level of guarantee I can continue to use the same tool as long as I want to. And I think we may just be getting to the point the open models are >= 5.6 Sol for coding.
I don't see how anyone can be using Claude with prices like this, it's pretty incredible what the OpenAI team is doing, w.r.t model quality and pricing.
Prices per 1M tokens Claude Opus 5.5 Claude Opus 5
Cache reads $0.20 $0.50
Input tokens $4 $5
Output tokens $20 $25
Cache writes $5 $6.25
These don’t necessarily reflect actual costs, OpenAI is not profitable and nowhere near. They’ve lost their market lead and Sam may feel they need to get it back with any means necessary.
GPT would charge more if they could. Both companies need way way more revenue. GPT simply made a calculation that they can earn more money by charging less than their competitors.
Any business would charge more if they could. Jevon's paradox would mean that they can make more money by charging less because demand is going to keep growing.
Ya, are LLM's not a great example of Jevon's paradox? I don't think Jevon's needs all else being equal. The paradox being that we should be able to use things less because they are more efficient, when instead they get used more.
Surely, a large part of the increase of the demand in LLMs is in their intelligence, but to hit the demand models needed to be made more efficient, and labs found that more efficient models, still demanded more usage.
They're cutting prices because they want to cannabalize the market for people using models like deepseek via API as well as people paying for anthropic subs.
When they cut prices on luna the first time around they took (literally) millions of users from anthropic.
Just because a provider is charging less, doesn't mean their cost went down. This is probably especially true with the big players that are trying to stay competitive.
A lot of what I'm doing has pretty expensive build/testing processes between iterations - even on a 40 core machine - so I'm not burning tokens 24/7 like some people may.
I'd guess I'm probably spending >50% of the time running tests & build processes & tooling and the remainder is purely burning tokens.
I also have some internal tooling (that I will hopefully open source soon) that makes LLMs substantially more correct (thus more efficient) - so there's that, too.
and anthropic won't? or any other inference provider? Running your own inference either locally or remotely are probably the only ways to make sure that doesn't happen.
And why is that bad? As your brain gets older, it will not remain so clever, so you'll be grateful for an AI that thinks like you do when it comes to your line of work.
You're building your livelihood/workflows on a set of inputs that you have no idea what they actually cost or how reliable they'll be when the VC cash stops flowing. If you're OK with that, do your thing but it seems a little foolish to me.
Not that anthropic models are very good at this, but due to the changes in tokenizers and thinking tokens: cost per token is not as helpful anymore as cost / task.
As someone who has used Claude Code and Codex the prices don't matter in the same way but I found that I burned through my usage way faster on Codex even though I regularly hear that the Codex plans go further. That was not my experience and the intelligence was comparable to what I was getting in Claude.
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.
I mainly use Codex/Sol to review my plans drafted by Fable. But beyond that, Astra blows through usage limits too fast to be a daily driver and writes weird code despite what my "house style" is, and Codex is behind Claude Code in terms of critical features like seeing what's going on in subagents.
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.
When I use these models in codex, there are two axes for me to control - the model and the reasoning level. I can use Astra, Sol, or Luna. And I can choose between 5 reasoning levels (light, medium, high, extra high, and ultra). What's the difference? As the problems that I want codex to solve get easier, should I turn down the model or the reasoning level? What's the difference between Astra medium and Luna high? So far I've just been leaving it on Astra and then turning the reasoning level up or down based on how hard I think the problem is.
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.
I would describe it as "fidelity" and "verbosity".
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?
there is no correct answer for that. One is the difference in size/params. The other is the amount of "rounds" of reasoning generating and reviewing what is generated.
Have they solved GPT5.6 SOL's propensity to over-engineer and over-complicate? You'd ask SOL to do something relatively simple, and find four single-use methods, an interface, and a factory-factory.
I actually preferred 5.6-Terra not because it is technically superior (it isn't) but because it had better instincts to NOT do this stuff.
PS - Speaking of better instincts, have they closed the UI-design gap at all? I keep a Claude subscription just because /design produces significantly higher quality UI design/UI feedback/UI refinement than anything I've seen from OpenAI.
Astra 6 was a huge improvement over Sol 5.6 for UI work. I haven't tried Sol 6 yet for it (it's only been a few minutes).
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.
Cutting prices by 50% as compared to 5.6 prices is exciting. GPT-6 Luna at $0.10/Mio input tokens and $0.50/Mio output is positively insane.
EDIT: this doesn't say anything about availability on either Azure or AWS. I'm assuming it will show up later, but it would be interesting if it didn't.
Artificial Analysis is reporting that 6 Luna scores 2 points lower on their coding index than 5.6 Luna, but is 60% cheaper:
> In the Coding Agent Index, Sol improves but Luna regresses: In OpenAI's Codex harness, GPT-6 Sol (max) scores 57 in the Artificial Analysis Coding Agent Index, up 2 points from GPT-5.6 Sol (max), with gains in Terminal-Bench 4.0 (43% vs 37%) and SWE-Atlas-QnA (58% vs 54%). At $2.99 per task it costs ~50% less than GPT-5.6 Sol (max) and sits on the Pareto frontier of Coding Agent Index vs Cost per Task. GPT-6 Luna (max) scores 41, down 2 points from GPT-5.6 Luna (max), with lower scores in SWE-Atlas-QnA (44% vs 49%) and DeepSWE v1.1 (64% vs 66%), at ~60% lower cost per task.
Given that they had to discontinue sales of the 20x Pro plan after the Astra release due to compute constraints, I wonder if 6 Sol & Luna are smaller vs their 5.6 counterparts?
The only two benchmarks shared between the Opus 5.5 and Sol 6 launch seem to be frontier code and automation bench, looks like Sol wins on automation bench (same performance for half the cost) and Opus 5.5 wins on frontier code (2-5% better scores across the board for same cost)
Since I spent my morning fixing a bug in my OpenAI API proxy that completely broke prompt caching and caused my usage limits to burn like kindling, really happy to see some of their new cache tooling:
Good. Maybe they can use GPT-6 to fix the accessibility of their iOS app. Output shows as text fields to VoiceOver, and the accessibility announcements have backslashes before seemingly every punctuation mark. And then bring accessibility announcements to the Android app so I don't have to make a whole new app just to add that through an accessibility service. Ugh the things I do for accessibility cause I'm blind. On a better note though, AI has done so much for the blind community, from image (and increasingly video) description to mods for video games like Final Fantasy 1 through 6 Pixel remaster, I have a ton to be grateful for.
I just switched from Claude to openAI. I'm surprised at how much easier it is to talk to. Claude always spoke to me with a suspicious side eye as if I was trying to do something naughty. For example I could not get it to help me get an old abandonware game running (sim tower).
Wow, gpt-5.6-Luna was already a fairly unbeatable bargain and now gpt-6-luna is both cheaper and better. And they did a phenomenal job getting gpt-6-sol to max out right where Astra begins; funny how they just so happened to avoid cannibalizing their best model while still being quite cost-competitive near the frontier.
At least it sounds good on paper, the the graphed results do give me pause as it seems the lower cost might come from a slightly nerfed base model combined with more thinking, going by the more erratic scoring curves and the lower no thinking baseline score. I’ll have to try it out but I really hope they haven’t nerfed Luna/Sol to make this price point possible!
I’m still finding context is king, even with the best models.
For example, I had Fable review Astra’s output yesterday, and it found some issues and fixed them. Passing the fixes back, Astra then uncovered additional issues with Fable’s fixes (and yes, this will go on ad infinitum if you let it, but these were “real” issues).
It seems the big story here is the reduced Luna pricing. It’s a fantastic model that can handle most automation needs (though I still use the big models for day-to-day development).
Per the benchmarks in the post, Luna 6 is at best a couple points superior to Luna 5.6 and (unless I’m reading it wrong) xhigh has actually degraded in quality?
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.
It's asking a lot to trust they can or will maintain this new pricing. In any case it's exciting to think this might lead to further price cuts in the highly competent and competitive Chinese clones. I'm still using ChatGPT for interactive queries, but at this point pretty much only because of its familiar UI
Well, they do rug pull constantly. This week and last leading up to this the cost to use Codex was overwhelmingly perceived as terrible. People running out of usage all over the place. Reddit full of people crying. I noticed it myself.
Then they do a new model launch, issue quota resets all around, and it's a party for 2-3 weeks before things return to normal.
SpaceX is a different beast with extremely high friction to enter its market, a massive technology lead, and well developed preferential high level relationships with just about every country worth worrying about.
OpenAI/Anthropic meanwhile feel a bit like they're hoping to sell iPhones in a market about to be flooded by $20 flip phones, with almost no channel of their own to do it. And for whatever mad reason OpenAI are now signalling they will attempt to compete on price with flip phones despite their cost of labour, energy, and just about everything else being far higher
AI needs to get rid of model versioning and model effort combinations. It's like selling an automatic transmission but still asking you to choose the gear, then after the trip telling you how much fuel you burned.
Nah, Luna uses was more tokens and fills the context up way to fast. Terra is in the sweet spot where if feels like Opus 4.6. Competent but not too smart. It also uses lets you have longer sessions (back and forth) without filling the context too fast.
I've found Astra to be horrible at making orchestration decisions. I will be trying to use Sol for both. Fable is very good at it though. Worst part of my week is when I hit my Fable usage limit and have to switch to Astra.
If I'm understanding correctly now when you want to use Codex to do a given task you need to decide between:
GPT-6 Luna (low medium high xhigh max ultra)
GPT-6 Sol (low medium high xhigh max ultra)
GPT-6 Astra (low medium high xhigh max ultra)
And then there's a fast mode toggle for all of it, too.
Not exactly a low-friction user experience!
Like are you supposed to just somehow intuit, “ah yeah, this task is definitely a GPT-6 Sol Medium task,” or something?
Is this just second nature for OpenAI employees? How are end users supposed to know how to optimally choose a model for a given task? Am I missing something completely here?
1. you can have luna clean up after itself and improve code 2. you might be doing something like video-editing, cad modeling, artistic direction, pcb routing, etc. that need to run a long time to "converge"
What a day! I couldn't really use the last Luna for much (wasn't smart enough) or Astra (too expensive). So this release is really exciting. I can probably use Sol 6 as much as I want in the week, which as great.
It wasn't really used enough and it sat in an awkward middle space between luna and sol where either luna high/xhigh or sol med were better cost/perf wise
It probably didn't see that much use, as it struggled to find a niche. If you wanted intelligence tasks, Sol was cheap enough and much smarter. If you wanted performance and cost-effectiveness, Luna was significantly better value while being only a little less intelligent.
Terra ended up just being an awkward middle ground that was not particularly suited for any workload.
Looking at their own charts it seems like it's only small incremental improvement over 5.6 Sol, but with a massive cost reduction. And the better writing/communication style that Astra had.
But the reason people say "Claude can't compete" is because Claude Opus has been going downhill since 4.7, and many have found Opus 5 intolerable. Fable is much better, but also much more expensive than OpenAI's offerings.
Is this comment about astroturfing or a decline in comment quality? To be honest, I was one of those early commenters, and I was just genuinely shocked at the price drop. I am also excited to try Opus 5.5!
Fundamentally I feel like coders just doesn't even need to be that smart anymore given AI assistance. This place ten years ago used to be filled with some of the most interesting comments/takes around for that reason.
I remember how a few months ago Dang was criticizing people for making comments like this. Guess he just realized how stupid that was and stopped bothering eventually.
Ya all these articles lately about how everyone is sick of reading AI prose, and interacting with models in general. Tons of new model optimizations and workflow optimizations or whatever. I'm not really aware of any idea or product aimed at making the internet usable, and making it somewhat resistant to the generated noise. I think HN is a bit better than reddit for this type of example for floods of comments, first movers on reddit REALLY rise to the top and stay there.
Are you trying to imply that nothing OpenAI can release would justify that response and therefore the people must be bots?
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.
This is the most blatantly astroturfed thread I have ever seen on Hacker News.
My previous comment--which suggested astroturfing--was the highest upvoted comment here until it got flagged. Which implies to me that atleast the other remaining humans on this forum see it as well.
26 minutes, 89 comments, upvoted instantly to the top, posted within one hour of the Opus 5.5 announcement. You tell me.
Do you think the "you can't mention astroturfing" rule is really serving HN these days? Do you think this thread hasn't been manipulated?
I respect you for replying here though, and yes I get that HN forum standards would suggest flagging my previous comment. But it is just sad to see a place used to be so vibrant get manipulated because of how much weight it holds for us in the industry.
And yea sure, I could go and flag all the bots and message Dang. But probably time to stop shouting into the void. :)
Yes, this thread is not being manipulated. People a) being excited about something and b) it being in favor of a certain company is not sufficient evidence of astroturfing.
I've seen your articles in the past and I thought they were great. So I respect your thinking, and have no intention of being combative.
But do you really think people were so excited about cheaper versions of Astra that they were just waiting around to comment the instant this was posted? More than two comments per minute? All the initial comments were really similar too: brief one liners celebrating the cheap prices.
I think AI right now is a sort of Rorschach test. What it is clearly revealing to me is that I don't trust organizations with enormous financial incentives to manipulate public opinion. So I see bots everywhere. :)
>Do you think the "you can't mention astroturfing" rule is really serving HN these days?
yes, i think so.
because, unfortunately, complaining about bots (or astroturfing, or whatever) doesn't stop them. so we end up with threads that have both the potential bot/astroturfing/whatever activity and complaints, which further drowns out any interesting comments.
Do you think all the comments in here are positive about the model? Because they aren't. In no way does it seem astroturfed. And yeah, pretty boring to read that kind of comment every time.
There's no evidence of astroturfing. The comments you’re referring to are from accounts with established history and in different locations, without any evidence of being linked to OpenAI. They just seem excited about the models and the pricing.
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.
GPT-6 Luna being half the price of GPT-5.6 Luna is a really big deal.
Here's GPT-6 Luna pelicans: https://tools.simonwillison.net/markdown-svg-renderer?url=ht...
And GPT-6 Sol: https://tools.simonwillison.net/markdown-svg-renderer?url=ht...
Scroll to the bottom for the GPT-6 Sol max one: https://tools.simonwillison.net/markdown-svg-renderer?url=ht...
For comparison, here are the pelicans I got for GPT-6 Astra: https://tools.simonwillison.net/markdown-svg-renderer?url=ht... - I still like the Astra Max one best.
Here's a comparison grid showing all of the GPT-6 and GPT-5.6 pelicans at all effort levels: https://static.simonwillison.net/static/2026/gpt-6-and-5.6.h...
The grid is actually really interesting, because it shows that the 5.6 family default to brighter colors than the 6 family.
The sol max looks like it's absolutely ripped for some reason
He’s been biking a lot
Looking at this, AI still has a long way to go. In Sol Max, the pelican's legs are missing on one side—how can one side have two pedals and two legs...
> GPT-6 Luna being half the price of GPT-5.6 Luna is a really big deal.
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.
6-luna is at the pareto for most of the tasks! I dont know how they make money here but its insane value from a closed source model. I'd go further and say it makes no sense (privacy, sovereignty etc aside) to use many other models as its not only expensive but also many providers don't have that much GPUs to serve at a significant volume. https://openrouter.ai/rankings?view=month#top-models 5.6 luna is already the most used model this month.
Can't agree more. Between 5.6 Luna and Gemini 3.8 flash I'm so happy for the value I'm getting for my dollar (subscription pricing not API pricing) :)
Gemini 3.8 Flash looks like its better than v7 Luna/Sol on DeepSWE v1.1 while at $0.75 per million input tokens and $3.75 per million output tokens. Luna is much cheaper, but Flash has nearly Astra's performance for under the price of Sol ($2/$10).
Not that this benchmark is super relevant anymore but these look worse than I expected.
Yeah, it's interesting how much worse they are than the Astra pelicans. I think that reflects a tiny bit of genuine value still left in the benchmark, to be honest.
When the Astra one was last time run? It's probably better to run these 2-4 weeks after release when models get nerfed to get idea of performance closer to what it is.
Isn't everyone pelican-maxxing these days?
He also blogged why he thinks it's still useful
How come the pelicans get older with more reasoning? Is GPT 6 taunting us with our mortality?
Is GPT-6 50% cheaper?
> 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
Yes, GPT-6 Luna is 50%-58% cheaper than GPT-5.6 Luna. (I think the blog text and graphs make it pretty clear.)
The table on https://developers.openai.com/api/docs/pricing is more readable:
Do you have a page showing all the pelicans you've ever created? Could be fun to browse - kinda like https://progress.openai.com/ but visual. (It's a shame they don't keep it updated)
I'm so tired of looking at benchmarks. I always look fwd to the pelicans.
https://simonwillison.net/tags/pelican-riding-a-bicycle/ but I need to build something better.
I find it very interesting that for both these models we such a clear progression of better images with higher thinking levels from 'hardly useful' to 'pretty nice'. I feel on many other models low and max are much closer.
At this point, the deciding factors for me between Claude Code 20x and Codex Pro 20x are:
1/ Usage limits: downstream of input/output cost, but resets and obscure windows and odd 20x plan / 5x plan != 4x usage math throw a wrench into it. Winner right now is Codex by a mile, especially when you factor in ChatGPT usage (even 6 Astra Pro) is essentially unmetered on the 20x plan. Always a bummer when asking if I should see a doctor about a rash means I can't code as much. It's also is a godsend if you use an MCP like oracle to automate the process of calling the Pro model on particularly tough problems, giving better planning results or deeper code analysis without burning usage.
2/ Context window in the harness. Claude Code wins on this. 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 (ETA: noname120 pointed out this is no longer the case and it can be enabled again [1]). 252k is just not enough. Codex's compaction is very good, fwiw, but it happens so frequently that even a model as powerful as Astra sometimes loses the plot on long-running tasks.
3/ Ability to use the plan outside of the official harness. Codex wins. Anthropic does shit like bills requests as extra usage if it sees a hermes.md in a commit.
I've subscription hopped a bunch, and at times I've had both, but I keep coming back to Codex because it wins on 2/3.
ETA: apparently I haven't been Keeping Up With the Altmans and new 20x signups have been disabled for a few weeks. I am grandfathered in, which makes the comparison above pretty much moot.
[1]https://news.ycombinator.com/item?id=49806060
I dunno about Codex-the-application itself, but you can definitely use e.g. Pi with the larger context windows with a Codex login. It puts a pretty large multiplier on credit usage, however.
I've been doing this, my only experience with codex was brutal usage wise and i just retreated back to pi pretty quickly so the credit usage i'm receiving is kinda all im familiar with. Surely seems like less than CC, but i guess not using codex makes my experience kinda not valid for comparing usage.
And ya i can go over that 240k limit, I still very seldom do, and try to treat it as the actual limit. I'm surprised to see so many people still talking about compaction to complete long running tasks, i think the bulk of the work should be somewhat frontloaded into a plan that is split off into subplans, then you can kinda open up a few options, one session with subagents for the subplans of the main plan, or just handoff prompts about progress against the main plan/relevant subplan. I just never trust the blackbox that is compaction, I feel its a recipe for disaster/context poison.
> It's also is a godsend if you use an MCP like oracle to automate the process of calling the Pro model on particularly tough problems
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
I actually haven't played with the GUI. I probably should now that the Linux version is in beta. My situation is kind of the reverse: I like using oracle to basically zip up my repo, ask GPT Pro to propose some sort of design or refactor based on the code, then provide a step by step implementation plan for a cheaper model to implement directly in a harness on my machine. It often takes upwards of 90 minutes to come up with something but I've never been disappointed by the results. I suppose I could do this and then save a step by referencing the oracle-created thread with the @ you mentioned
And re: the toml workaround, AWESOME! I appreciate you pointing these two things out, this is my highest-ROI HN comment thus far.
In my personal experience I currently get a lot, lot more usage on the 5x Claude plan than the 5x Codex plan.
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.)
I've been using Claude Pro and recently gave Codex a try again. Both on the $20 plans. I get so much more usage with Claude. It's night and day for me. Codex runs out constantly, whereas Claude I hit limits very rarely.
Assuming you are doing coding, I'm curious how would you characterize tne majority of your work (language, domain, frontend/backend, etc)?
> Winner right now is Codex by a mile
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 is my experience. After months of hearing how Codex limits were way higher I bumped to the $100/mo plan after hitting my limits a day early on Claude due to some heavy usage + Fable (not normal for me, I often fit nicely in the $200/mo plan). I hit the usage limit in a day with a single agent running on codex and the tiny context window was stifling. Yes, I'm comparing a $100 to a $200 plan but I extrapolated the usage (4x'd it) and it still wasn't close, I got way more done with Opus.
Using Agentsview (which might have it's own issues) I was getting ~$200 of API usage in my 1 week Codex window (paid $100) vs ~$5,000 of API usage in 1 week for Claude (paid $200).
What are you talking about? ChatGPT unmetered? No way! That was 2 months ago perhaps and it’s possible your account still hasn’t gotten the new limits. I noticed around 1 month ago I was still going full throttle on my codex subscription and my limits were barely budging, and then all of sudden people around me started to complain about limits. I thought they’re crazy, but then my account go the hammer, and that was it. If I have the same pattern of usage like I did before, basically having an agent working continuously on a coding take, my weekly limit goes in 2 days.
Interesting, rolling out new limits would explain a lot. Where did you hear this? I wonder if they detect users with multiple accounts and do that first.
On usage in ChatGPT settings, I see: Plan limits Shared across Codex, Work, Workspace Agents, and ChatGPT for Excel. Chat conversations are not included.
Is this not the default anymore? I am on the (now closed) 20x plan.
Codex/ChatGPT Pro 20x isn't really a thing now, they have disabled it a week or two ago.
Not that I disagree that Codex wins out, but the deciding factor actually is - Codex Pro 20x is not available for purchase, indefinitely. So, what's the point of this discussion? People who already have the 20x sub are unlikely to cancel, and the rest of us can't access it.
theres a popular thread on claudecode or claudai subreddit that proves 20x isnt really 20x. apparently its a marketing gimmick and the recommended solution is two 5x plans > 20x at greater than half the cost of the 20x
> Usage limits [...] Winner right now is Codex by a mile
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
> you can't buy a $200 sub anymore
Are you sure?
Yes.
https://x.com/thsottiaux/status/2098113585683808624
I’ve been a Claude user, switched to Codex expecting usage limits to be more loose but I can’t even get through a basic sysadmin task on the $20 plan using Sol medium before I hit the 5hr one.
I think I’m gonna move back to a Claude plan. I could barely hit the $200 limit if I went non-stop on programming tasks.
Maybe it's due to 20x / 5x != 4 but I have the $200/mo Claude and $100/mo Codex and I get _way_ less usage on Codex, well under 1/4th the usage. In 1-2 days of semi-heavy _single_ agent usage with Sol High I can burn through my whole week of Codex. Again, this is not running multiple agents, just 1 at a time.
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.
Same experience. Have both subs. It's just not true anymore that Codex gives you more usage than Claude.
Makes me think they picked Codex, stopped trying Claude, and just hang on to outdated beliefs about the value they're receiving.
> Claude Code 20x and Codex Pro 20x
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.
You’re sharing outdated info
Care to be specific? 20x is closed. And the 2x pricing is literally on the pricing sheet for gpt-6 astra, sol and luna.
Also, OpenAI is just a company I'd rather support than Anthropic.
While you're understandably not including the values of the $20 standard plans on both, I find the generosity of then token limits on ChatGPT plus vs Claude Pro (it's a huge difference) to be good representation of their respective attitudes towards the average user. You literally cannot use Claude pro to build real software, unless you're extremely frugal with your prompts and don't try anything even a little ambitious.
Also, Anthropic has zero models comparable to Luna.
Reasons for this?
> Also, OpenAI is just a company I'd rather support than Anthropic.
Astra planner/designer with Sol+Luna subagents has worked well for me to improve context continuity. Luna generates code, Sol reviews code and runs/monitors integration/E2E tests. It's about 20% more usage efficient and 20% faster to finish tasks. I've been very subagent-skeptic for a while but the economics of codegen with Luna have made it click. This just works in Codex with a single-line AGENTS.md instruction.
> Ability to use the plan outside of the official harness. Codex wins. Anthropic does shit like bills requests as extra usage if it sees a hermes.md in a commit.
I'm quite puzzled about why Anthropic is so hellbent on blocking other coding agent. It's not like Claude Code has any secret sauce, right? And does Anthropic make monkey off API usage, and their magic is on the model side anyway?
Usage is actually Claude now because of Opus 5.5 since it a better model that Astra. I maxed out my 200$ Claude plan with 10b token on Opus 5 and 5.5 is cheaper. I maxed out two Codex accounts with like not even 5b tokens.
I've been working with agents all year, but 5.6 Sol was some sort of sweet spot for me. Something about how it communicated verbally and its engineering instincts just clicked for me, and I was able to somehow predict it and jam with it. Like a colleague you click with. It's the first model I've gotten attached to. I'm concerned that whatever model supercedes it, while technically better, just won't feel quite as natural to work with. And this makes me feel very professionally vulnerable to the labs. I miss the days when my crucial tooling came from companies as reliable and predictable as, say, Jetbrains.
Same. In fact I found 6 Astra to be a downgrade in situations where I didn't need the extra intelligence.
Yeah.
Astra was/is superior for planning type tasks. It was capable of doing seemingly magic things with rather vague/lazy instructions ("I need to be able to test this on Windows, maybe a qemu VM or something? Shrug." ... 1 hour later "yeah i built you a whole qemu + eval windows image + harness of powershell scripts + shell scripts to retrieve & verify harness.").
And for UI work -- which is not something I do a lot of but do here and there -- it was clearly superior to 5.6 Sol.
But it also feels sloppier? Somehow. And too expensive to use.
We'll see how Sol 6 is.
I felt this way with Sol in the 5.6 series and was one of the seemingly few people on this earth who liked Terra for that reason. I would often have a very specific code-manipulation ask, e.g. "add a parameter to this method, ensure all callers pass it in, if there is not a logical way to derive the parameter to be passed in a particular instance, flag this in your final response", and Sol would go on some rabbit hole side quest to refactor my codebase to determine some way to derive it rather than flagging it as I had asked.
Terra had the "workhorse" quality where it could do these changes in bulk and follow directions without being too 'smart' (but sloppy) as you described. Luna was a bit too dumb and would make sloppy mistakes; I see that more as a "run these tests and format the results" sort of model. Maybe 6 Luna will be better.
I also just reread your comment and realized the naming convention is still extremely confusing with respect to ordering of [Family]x[Model]x[Number].
Glad you pointed out the UI work. I've been doing a lot of it and it's so much better than 5.6 as UI, it's unbelievable. I give it super ambiguous instructions and it's reading my mind. I do the same thing with 5.6 and I'm correcting it for a few minutes.
Completely agree. I've been using 5.6 still even with Astra available to me for most tasks. It's funny how much of this is just "vibes" because I cannot quantify what it is. Astra is definitely better when I have an ambitious feature, but in like 9/10 tasks I prefer working with 5.6 Sol. A few weeks ago when the limits were seemingly higher, having 5.6 on fast mode was a good time.
This is 100% my experience. I rarely reach for Astra as we speak.
It's a shame the labs don't open source their models after deprecating them. I get why, but, it's a piece of internet history I hope is preserved.
I agree. Sol followed my instructions well and wrote good code.
This has been my experience for a year. Same with Opus models. This is how I think this tech will be best used in the long term - finding the one you vibe with most. Much like IDEs!
Not only was 6 worse the 5.6 Sol for my me, but it went through my Plus usage in minutes, while I could cruise for hours with 5.6. It would churn on a basic prompt for minutes and then just give up on usage limits.
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.
I had this experience as well, but after rewriting my agent instructions it has been far better. I believe Astra’s “token efficiency” translates to “don’t research as much” which caused it to make poorly informed architectural decisions.
Similar for me. gpt-5.6-sol high has been my go-to for months. One of the reasons I'm pushing myself to try open models more is because it lends some level of guarantee I can continue to use the same tool as long as I want to. And I think we may just be getting to the point the open models are >= 5.6 Sol for coding.
I don't see how anyone can be using Claude with prices like this, it's pretty incredible what the OpenAI team is doing, w.r.t model quality and pricing.
Model
Input
Output
Price reduction
GPT‑6 Sol vs. GPT‑5.6 Sol
$4 → $2
$20 → $10
50% cheaper
GPT‑6 Luna vs. GPT‑5.6 Luna
$0.20 → $0.10
$1.20 → $0.50
50% cheaper
These don’t necessarily reflect actual costs, OpenAI is not profitable and nowhere near. They’ve lost their market lead and Sam may feel they need to get it back with any means necessary.
The last time I gave GPT a shot, it ate all my tokens and got nothing meaningful done.
A vs B
Should be B vs A correct?
Else it's confusing
GPT would charge more if they could. Both companies need way way more revenue. GPT simply made a calculation that they can earn more money by charging less than their competitors.
Any business would charge more if they could. Jevon's paradox would mean that they can make more money by charging less because demand is going to keep growing.
FWIW, what you're describing is a simple demand curve, not Jevons paradox.
The "paradox" is when an increase in efficiency which would decrease the use of a resource all else equal, instead indirectly causes more use.
Ya, are LLM's not a great example of Jevon's paradox? I don't think Jevon's needs all else being equal. The paradox being that we should be able to use things less because they are more efficient, when instead they get used more.
Surely, a large part of the increase of the demand in LLMs is in their intelligence, but to hit the demand models needed to be made more efficient, and labs found that more efficient models, still demanded more usage.
Of course they'd charge more if they could... Of course they're pricing to outcompete their competitor...
They also have postponed their IPO. So they don't have to be profitable that soon. Anthropic on the other hand plans to do the IPO this fall.
HN discovers competition leads to lower prices
They're cutting prices because they want to cannabalize the market for people using models like deepseek via API as well as people paying for anthropic subs.
When they cut prices on luna the first time around they took (literally) millions of users from anthropic.
Opus 5.5 is incredible so far, its going to get used. Fable is much better than Astra for me in practice, and Sol is not marketed as better.
Its a great release, I will use both heavily.
For API usage, sure. But plenty of people have subscriptions where these differences effectively don’t matter.
It should matter; if their costs go down you'll get more usage.
Just because a provider is charging less, doesn't mean their cost went down. This is probably especially true with the big players that are trying to stay competitive.
Also, batch processing prices are still 50% off, which put GPT-6 Sol and GPT-6 Luna at $5 and $0.25 for output.
https://developers.openai.com/api/docs/pricing?latest-pricin...
I could already run Sol High on 3 concurrent side projects 24/7 and not run out of quota.
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.
How much does it cost you per month to have that much sol high usage and what do you use, api? Through what? Thank you
they said quota so i would imagine the $200 subscription. Probably through Codex or Pi coding agents.
$200/mo
A lot of what I'm doing has pretty expensive build/testing processes between iterations - even on a 40 core machine - so I'm not burning tokens 24/7 like some people may.
I'd guess I'm probably spending >50% of the time running tests & build processes & tooling and the remainder is purely burning tokens.
I also have some internal tooling (that I will hopefully open source soon) that makes LLMs substantially more correct (thus more efficient) - so there's that, too.
You can now start to add automations on top of typical dev flows.
There are a ton of use cases that open up with cheaper models.
E.g. extensive security scanning on every PR, quality scans, adversarial reviews etc
>> GPT‑6 Sol vs. GPT‑5.6 Sol
>> $4 → $2
>> $20 → $10
Do you mean 100% more expensive? GPT 6 is 100% more expensive than 5.6 per your post.
It's before and after following the arrow. 6 is the cheaper one.
Yes very poor proofreading!
This is how the price cut is portrayed on OpenAI’s site. They are trying to say the prices have moved from the higher ones to the lower ones.
You also need to compare allowances on Codex vs. Claude Code
Wtf is GPT-6 Sol, I though GPT-6 is Astra?
Number is generation Name is the size (Luna smallest to Astra largest)
Then what is Astra high-extra high-Ultra? That’s effort within each tier?
Exactly
Yes that is number of reasoning tokens used.
Performance increases both with larger model (Luna vs Sol)
And with more reasoning (low vs xhigh)
Disagree. I would never use OpenAI cause they're probably just going to steal whatever I'm working on.
and anthropic won't? or any other inference provider? Running your own inference either locally or remotely are probably the only ways to make sure that doesn't happen.
Well we know for a fact that OpenAI steals Millennium Problem work from researchers. Have we seen anything similar from Anthropic?
source? p sure they said they were confident they did not access the researcher's chats
What are you working on? Is any of it actually worth stealing?
And why is that bad? As your brain gets older, it will not remain so clever, so you'll be grateful for an AI that thinks like you do when it comes to your line of work.
>so you'll be grateful for an AI that thinks like you do when it comes to your line of work.
Highly subjective take
What kind of work do you do, out of curiosity
Are you really comparing LLMs to brains?
See I will never use anthropic because they run inference on spacex. Wat den een sien Uhl, is den annern sien Nachtigall.
These are the pre rug pull prices. They'll increase prices 10x and nerf the models after they IPO.
Before IPO. This is why Anthropic isn't playing the same games
there are still competitive market forces for co's post IPO
Okay? I didn’t sign a 10 year contract. We’re month to month and I use my own harness.
If they’re subsidizing my usage, that’s great.
You're building your livelihood/workflows on a set of inputs that you have no idea what they actually cost or how reliable they'll be when the VC cash stops flowing. If you're OK with that, do your thing but it seems a little foolish to me.
Not that anthropic models are very good at this, but due to the changes in tokenizers and thinking tokens: cost per token is not as helpful anymore as cost / task.
As someone who has used Claude Code and Codex the prices don't matter in the same way but I found that I burned through my usage way faster on Codex even though I regularly hear that the Codex plans go further. That was not my experience and the intelligence was comparable to what I was getting in Claude.
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.
I mainly use Codex/Sol to review my plans drafted by Fable. But beyond that, Astra blows through usage limits too fast to be a daily driver and writes weird code despite what my "house style" is, and Codex is behind Claude Code in terms of critical features like seeing what's going on in subagents.
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.
> 50% cheaper
Did cache read/write also decrease by 50% or similar? That's where most (95%+) of the cost is for agentic coding workloads.
I legit question if these prices are still inference-profitable for OpenAI. They likely didn't have 100% profit margin.
When I use these models in codex, there are two axes for me to control - the model and the reasoning level. I can use Astra, Sol, or Luna. And I can choose between 5 reasoning levels (light, medium, high, extra high, and ultra). What's the difference? As the problems that I want codex to solve get easier, should I turn down the model or the reasoning level? What's the difference between Astra medium and Luna high? So far I've just been leaving it on Astra and then turning the reasoning level up or down based on how hard I think the problem is.
Ya it’s annoying to have to manage this.
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.
For easy problems, just use Luna on max level. It has so much token mileage you can go forever.
I would describe it as "fidelity" and "verbosity".
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?
there is no correct answer for that. One is the difference in size/params. The other is the amount of "rounds" of reasoning generating and reviewing what is generated.
Have they solved GPT5.6 SOL's propensity to over-engineer and over-complicate? You'd ask SOL to do something relatively simple, and find four single-use methods, an interface, and a factory-factory.
I actually preferred 5.6-Terra not because it is technically superior (it isn't) but because it had better instincts to NOT do this stuff.
PS - Speaking of better instincts, have they closed the UI-design gap at all? I keep a Claude subscription just because /design produces significantly higher quality UI design/UI feedback/UI refinement than anything I've seen from OpenAI.
Astra 6 was a huge improvement over Sol 5.6 for UI work. I haven't tried Sol 6 yet for it (it's only been a few minutes).
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.
Cutting prices by 50% as compared to 5.6 prices is exciting. GPT-6 Luna at $0.10/Mio input tokens and $0.50/Mio output is positively insane.
EDIT: this doesn't say anything about availability on either Azure or AWS. I'm assuming it will show up later, but it would be interesting if it didn't.
Does API price cut translate into higher allowance on the subscription? Do we know?
It does, usually. Luna seems like almost infinite on the 20x plan, and that’s reflected in the API price. Isn’t that the case for all providers?
I’d rather keep 5.6 Sol, and get that even more optimized. I’m not sure I’ll like 6 Sol if it’s anything like Astra.
they're already on bedrock
Artificial Analysis is reporting that 6 Luna scores 2 points lower on their coding index than 5.6 Luna, but is 60% cheaper:
> In the Coding Agent Index, Sol improves but Luna regresses: In OpenAI's Codex harness, GPT-6 Sol (max) scores 57 in the Artificial Analysis Coding Agent Index, up 2 points from GPT-5.6 Sol (max), with gains in Terminal-Bench 4.0 (43% vs 37%) and SWE-Atlas-QnA (58% vs 54%). At $2.99 per task it costs ~50% less than GPT-5.6 Sol (max) and sits on the Pareto frontier of Coding Agent Index vs Cost per Task. GPT-6 Luna (max) scores 41, down 2 points from GPT-5.6 Luna (max), with lower scores in SWE-Atlas-QnA (44% vs 49%) and DeepSWE v1.1 (64% vs 66%), at ~60% lower cost per task.
https://x.com/ArtificialAnlys/status/2102462962758033624
Given that they had to discontinue sales of the 20x Pro plan after the Astra release due to compute constraints, I wonder if 6 Sol & Luna are smaller vs their 5.6 counterparts?
Yup more like a 5.7 than a 6
Can we trust AA anymore after the last debacle a week or two ago?
The only two benchmarks shared between the Opus 5.5 and Sol 6 launch seem to be frontier code and automation bench, looks like Sol wins on automation bench (same performance for half the cost) and Opus 5.5 wins on frontier code (2-5% better scores across the board for same cost)
Since I spent my morning fixing a bug in my OpenAI API proxy that completely broke prompt caching and caused my usage limits to burn like kindling, really happy to see some of their new cache tooling:
* Prompt caching dashboard: https://platform.openai.com/usage?usage_section=prompt-cachi...
* Adjust reasoning effort and tool availability without breaking cache
I'm glad both labs noticed and are trying to improve the models communication styles, they were getting closer and closer to meaningless gibberish.
Good. Maybe they can use GPT-6 to fix the accessibility of their iOS app. Output shows as text fields to VoiceOver, and the accessibility announcements have backslashes before seemingly every punctuation mark. And then bring accessibility announcements to the Android app so I don't have to make a whole new app just to add that through an accessibility service. Ugh the things I do for accessibility cause I'm blind. On a better note though, AI has done so much for the blind community, from image (and increasingly video) description to mods for video games like Final Fantasy 1 through 6 Pixel remaster, I have a ton to be grateful for.
I just switched from Claude to openAI. I'm surprised at how much easier it is to talk to. Claude always spoke to me with a suspicious side eye as if I was trying to do something naughty. For example I could not get it to help me get an old abandonware game running (sim tower).
Wow, gpt-5.6-Luna was already a fairly unbeatable bargain and now gpt-6-luna is both cheaper and better. And they did a phenomenal job getting gpt-6-sol to max out right where Astra begins; funny how they just so happened to avoid cannibalizing their best model while still being quite cost-competitive near the frontier.
At least it sounds good on paper, the the graphed results do give me pause as it seems the lower cost might come from a slightly nerfed base model combined with more thinking, going by the more erratic scoring curves and the lower no thinking baseline score. I’ll have to try it out but I really hope they haven’t nerfed Luna/Sol to make this price point possible!
I’m still finding context is king, even with the best models.
For example, I had Fable review Astra’s output yesterday, and it found some issues and fixed them. Passing the fixes back, Astra then uncovered additional issues with Fable’s fixes (and yes, this will go on ad infinitum if you let it, but these were “real” issues).
It seems the big story here is the reduced Luna pricing. It’s a fantastic model that can handle most automation needs (though I still use the big models for day-to-day development).
Does anyone know if the ~50% price reduction also implies x2 subscription usage? Or is it only for the API.
Edit: Yes, it applies also to subscriptions, source https://x.com/thsottiaux/status/2102463847714247142
I've been raving about Luna 5.6 as it's dirt cheap, and "intelligent enough". Double quoted.
Now GPT 6 Luna is even cheaper, and more intelligent, there is no going back... to SOL 5.6 for intelligent layer.
Per the benchmarks in the post, Luna 6 is at best a couple points superior to Luna 5.6 and (unless I’m reading it wrong) xhigh has actually degraded in quality?
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.
Not only is GPT-6 Luna better, it's 50% cheaper. It was already practically free on a pro plan.
Good that they reduced the pricing, since they have closed the 20x plan, and Tibo has stated on X you're expected to pay API/credit prices now.
Unsure if 5x + credits is a good value compared to Claude 20x.
OpenAI, Antrophic and others are operating with 80% margins. They can lower the prices for a long while.
Source?
You probably mean they are operating with 80% margins discounting training expenses, which will continue to be pretty high for the foreseeable future.
Opus 5.5 seems better? Can someone attach both scores
Not the direct competitor to Opus 5.5, cuz 6 Sol is 50% cheaper.
Same price on Cache Reads 0.2/M So won't be 50 percent cheaper, more like 25% cheaper assuming half cost is cache read.
cost is dominated by non cached reads
that might depend on usecase, half of my cost is cache reads usally
It's asking a lot to trust they can or will maintain this new pricing. In any case it's exciting to think this might lead to further price cuts in the highly competent and competitive Chinese clones. I'm still using ChatGPT for interactive queries, but at this point pretty much only because of its familiar UI
Curious why you think it's unsustainable?
Well, they do rug pull constantly. This week and last leading up to this the cost to use Codex was overwhelmingly perceived as terrible. People running out of usage all over the place. Reddit full of people crying. I noticed it myself.
Then they do a new model launch, issue quota resets all around, and it's a party for 2-3 weeks before things return to normal.
Oh, I'm happy I'm not the only one. Astra was feasting on tokens!
It wasn't just Astra. Sol 5.6 was a hog, too. They futzed with the formula and it pissed people off royal.
Because at some point keeping it up involves filing an S-1 that doesn't look like a garbage fire
Didn't SpaceX already set a precedence for garbage fire S-1s? I don't think OpenAI has to worry about that?
SpaceX is a different beast with extremely high friction to enter its market, a massive technology lead, and well developed preferential high level relationships with just about every country worth worrying about.
OpenAI/Anthropic meanwhile feel a bit like they're hoping to sell iPhones in a market about to be flooded by $20 flip phones, with almost no channel of their own to do it. And for whatever mad reason OpenAI are now signalling they will attempt to compete on price with flip phones despite their cost of labour, energy, and just about everything else being far higher
AI needs to get rid of model versioning and model effort combinations. It's like selling an automatic transmission but still asking you to choose the gear, then after the trip telling you how much fuel you burned.
No terra it seems? Luna 5.6 is great for token churning so it will be exciting to try the new one.
Perhaps people realized that Luna Max is ~ Terra?
Nah, Luna uses was more tokens and fills the context up way to fast. Terra is in the sweet spot where if feels like Opus 4.6. Competent but not too smart. It also uses lets you have longer sessions (back and forth) without filling the context too fast.
Terra is the middle-child in more ways than one. It has much lower usage than Sol or Luna (going off OpenRouter).
6 Sol Performs worse than 5.6 Sol at DeepSwe?
Wierd!!
Luna really is "intelligence to cheap to meter" by now
Wouldn't that mean the cost of metering it is more than they make from metering it? I don't think that is the case.
This Luna pricing is obscene man. 5.6 was good enough for so many use cases (data analysis, structured extraction etc).
Incredible.
Hello, I'm Elliot. You need to delete your AI servers or I'll do it myself.
Love the price reductions across major players
Because Qwen4 has been announced!
and to squeeze anthropic, and other research innovations, not just chinese models but those help bring price down
And GLM 5.3 works great
It looks like the optimal pattern is to have Astra as the orchestrator and Sol as the implementer. Same as with Fable and Opus.
I've found Astra to be horrible at making orchestration decisions. I will be trying to use Sol for both. Fable is very good at it though. Worst part of my week is when I hit my Fable usage limit and have to switch to Astra.
I've found Sol to be an excellent orchestrator, with Astra the planner and Sol again the implementer.
If I'm understanding correctly now when you want to use Codex to do a given task you need to decide between:
And then there's a fast mode toggle for all of it, too.
Not exactly a low-friction user experience!
Like are you supposed to just somehow intuit, “ah yeah, this task is definitely a GPT-6 Sol Medium task,” or something?
Is this just second nature for OpenAI employees? How are end users supposed to know how to optimally choose a model for a given task? Am I missing something completely here?
So opus 5.5 has reduced price. Who is winning then?
Live notification in Codex:
> GPT-5.6-Sol is retiring. This conversation will automatically switch to GPT-6-Sol
I don't recall OAI retiring a model so early lol. Similar arch?
Pricing is insane, can have Luna going after a goal for 10 days and not run into maxing out the limits.
Why would you do this though, surely these long running /goal tasks just like letting a wild animal out into your code base.
Does anyone care about code quality anymore?
1. you can have luna clean up after itself and improve code 2. you might be doing something like video-editing, cad modeling, artistic direction, pcb routing, etc. that need to run a long time to "converge"
Luna is fine. It's not Claude Sonnet 3.5.
RIP Terra
There's no way this wasn't meant to coincide with Anthropic's release today.
They hinted this release last week for tuesday already, so if anything it would be Anthropic that tried to make this happen. But I doubt it.
Altman said it was launching last week on twitter, but they pushed it back to this week
What a day! I couldn't really use the last Luna for much (wasn't smart enough) or Astra (too expensive). So this release is really exciting. I can probably use Sol 6 as much as I want in the week, which as great.
Code deception 10% at 5.6 to 1.3% for 6.0? So models are getting more safe rather than less safe? hmmm
Gpt 6 Luna is cheaper than Deepseek 4.1 flash! Today is wild in terms of intelligence/price across the board!
I dont understand why there is not a gpt-6 terra?
It wasn't really used enough and it sat in an awkward middle space between luna and sol where either luna high/xhigh or sol med were better cost/perf wise
I don't agree. In "none" thinking mode, Terra serves a useful purpose where medium-grade intelligence is needed. Luna doesn't cut it.
It probably didn't see that much use, as it struggled to find a niche. If you wanted intelligence tasks, Sol was cheap enough and much smarter. If you wanted performance and cost-effectiveness, Luna was significantly better value while being only a little less intelligent.
Terra ended up just being an awkward middle ground that was not particularly suited for any workload.
The users of Terra disagree. Specifically, Terra is useful when medium-grade intelligence is needed in instant ("none" thinking) mode.
I have found it worked quite well as the workhorse model in my hermes agent.
I read that there are rumors that they're getting rid of that tier. No idea where the rumor came from, though. This lends credence to it, I suppose.
I'm scared now, my employer only allows Luna and Terra on 5.6. I really hope they will allow Sol then on GPT 6.
Funny thing is they very recently also set a real limit per-user/month, so why even limit the models because theyre "too expensive".
Sol price is halved so no need for terra
Why is Claude missing on the "Factuality" graph?
so opus 5.5 is smarter and cheaper than fable, and sol 6 is a little dumber and WAY cheaper than astra? is that right?
Sol 6 is also dumber than Sol 5.6 on some tasks (DeepSWE)
Third-party inference providers will have a hard time to beat Luna in pricing with comparable open models.
Would be funny if Google drops Gemini 4 today.
Very nice in cost/1mtok. Looks like more work is being done for efficient everyday helper models as time goes on.
Looking at their own charts it seems like it's only small incremental improvement over 5.6 Sol, but with a massive cost reduction. And the better writing/communication style that Astra had.
Which... fine, I'll take that.
Luna is the goat for real, cost intelligence ratio is insane already and it is enough for most daily computer use.
[flagged]
And comments complaining about other comments too
and comments complaining about other comments complaining too
Pretty sure this is the reason HN exists ¯\_(ツ)_/¯ lol
Including this one, yes.
But the reason people say "Claude can't compete" is because Claude Opus has been going downhill since 4.7, and many have found Opus 5 intolerable. Fable is much better, but also much more expensive than OpenAI's offerings.
And comments complaining about how only big businesses get benefitted too
Is this comment about astroturfing or a decline in comment quality? To be honest, I was one of those early commenters, and I was just genuinely shocked at the price drop. I am also excited to try Opus 5.5!
In the other hand the pricies dropped by a big margin
bots everywhere
Welcome to the new internet. It was fun whilst it lasted. Next evolution will likely be closed, invite only forums.
Eternal September 2, I suppose.
They already exists. You haven’t been invited? Hmmmmm
Fundamentally I feel like coders just doesn't even need to be that smart anymore given AI assistance. This place ten years ago used to be filled with some of the most interesting comments/takes around for that reason.
It’s not that bad: https://news.ycombinator.com/bestcomments
Stick with it. The collapse of HN is a leading indicator to the fall of humanity.
I remember how a few months ago Dang was criticizing people for making comments like this. Guess he just realized how stupid that was and stopped bothering eventually.
The comment got flagkilled, I'm unsure what else dang would need to do.
Are the prices very nice or not?
Ya all these articles lately about how everyone is sick of reading AI prose, and interacting with models in general. Tons of new model optimizations and workflow optimizations or whatever. I'm not really aware of any idea or product aimed at making the internet usable, and making it somewhat resistant to the generated noise. I think HN is a bit better than reddit for this type of example for floods of comments, first movers on reddit REALLY rise to the top and stay there.
Are you trying to imply that nothing OpenAI can release would justify that response and therefore the people must be bots?
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.
The new default is 6.0 Sol high. Escalate to Astra-medium. If usage is tight go luna6.0-max
sage
Selling dollar bills for $0.40 to undercut the guys selling them for $0.50 is a bold move. Let's see if it pays off for them.
As a user of 5.6-Terra, I am sick and tired of the inconsistencies in GPT model families. There is no 6-Terra.
They dropped Terra because it was worse than Luna / Sol at every point of cost performance curve.
I can already see it. 7-Nebula, 8-Galactic, 9-Cosmos; The size inflation is real.
Well at least it looks like OpenAI is dogfooding because their announcements, product names, and everything else looks and sounds like LLM-slop.
This is the most blatantly astroturfed thread I have ever seen on Hacker News.
My previous comment--which suggested astroturfing--was the highest upvoted comment here until it got flagged. Which implies to me that atleast the other remaining humans on this forum see it as well.
26 minutes, 89 comments, upvoted instantly to the top, posted within one hour of the Opus 5.5 announcement. You tell me.
>My previous comment--which suggested astroturfing--was the highest upvoted comment here until it got flagged
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.)
Do you think the "you can't mention astroturfing" rule is really serving HN these days? Do you think this thread hasn't been manipulated?
I respect you for replying here though, and yes I get that HN forum standards would suggest flagging my previous comment. But it is just sad to see a place used to be so vibrant get manipulated because of how much weight it holds for us in the industry.
And yea sure, I could go and flag all the bots and message Dang. But probably time to stop shouting into the void. :)
I agree with the rule and also found your comment boring.
Also, I don’t see that much astroturfing here? (And I tend to see it a lot on HN.)
Yes, this thread is not being manipulated. People a) being excited about something and b) it being in favor of a certain company is not sufficient evidence of astroturfing.
I've seen your articles in the past and I thought they were great. So I respect your thinking, and have no intention of being combative.
But do you really think people were so excited about cheaper versions of Astra that they were just waiting around to comment the instant this was posted? More than two comments per minute? All the initial comments were really similar too: brief one liners celebrating the cheap prices.
I think AI right now is a sort of Rorschach test. What it is clearly revealing to me is that I don't trust organizations with enormous financial incentives to manipulate public opinion. So I see bots everywhere. :)
Yes. See my comment on Bluesky: https://bsky.app/profile/did:plc:oxaernim5mj2mmy3ytrvb42n/po...
> what the fuck
>Do you think the "you can't mention astroturfing" rule is really serving HN these days?
yes, i think so.
because, unfortunately, complaining about bots (or astroturfing, or whatever) doesn't stop them. so we end up with threads that have both the potential bot/astroturfing/whatever activity and complaints, which further drowns out any interesting comments.
That is actually a great point. I have no rebuttal.
Do you think all the comments in here are positive about the model? Because they aren't. In no way does it seem astroturfed. And yeah, pretty boring to read that kind of comment every time.
There's no evidence of astroturfing. The comments you’re referring to are from accounts with established history and in different locations, without any evidence of being linked to OpenAI. They just seem excited about the models and the pricing.
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