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Advancing the price-performance frontier with GPT‑5.6
- xendo 2mo agoDoes that also increase the token count in their subscription like ChatGPT GO?
- dgellow 2mo agoHow is that economically possible? I’m so confused by those prices
- anthonypasq 2mo agohow many times do you have to be metaphorically hit in the head with a brick before you realize inference margins at api pricing were 80%+
- brazukadev 2mo agoI was metaphorically hit in the head with the brick of already provisioned computing with a lot less demand than anticipated by multiple MoUs.
- svieira 2mo agoSo, does that mean they're selling tokens at cost? Or that they realized they were doing 180% more work than necessary and they're passing the savings on because "your margin is my opportunity" and this is a dog-eat-dog fight, but 80% margins are nice, no one needs multiple hundreds?
- simianwords 2mo agoI genuinely don’t get why you will not accept the simplest explanation? They found efficiencies? Why all these contrived explanations??
- dgellow 2mo agoUh… are you okay? That’s a completely disproportionate, aggressive tone. How is that warranted
- simianwords 2mo agoDisproportionate yes but you seem still confused on how it’s economically possible when 1. The basic mechanism is literally described in the post: they found efficiencies and passed it down 2. This has been the trend for all the time LLMs have existed Why confusion then? What’s surprising you?
- spacebacon 2mo ago[dead]
- bakugo 2mo ago> GPT‑5.6 Luna, our fastest and most affordable model, will cost 80% less Looks like the Chinese models are really making a dent. Having 3 different price categories with the "most affordable" one still costing more than GLM 5.2 never made sense.
- measurablefunc 2mo agoIt all comes back to electricity cost. China has cheaper electricity so as long as China keeps pace there is no way for American companies to undercut them. Each boolean operation in China is cheaper than the one in America. > China: Household rates average around $0.08 / kWh (¥0.53/kWh). vs > US: Household rates average around $0.16 / kWh, though regional variation is massive—ranging from ~$0.10/kWh in low-cost states (like Washington or Louisiana) to $0.30–$0.45+/kWh in high-cost areas like California or Hawaii.
- cbg0 2mo agoThis doesn't seem correct. Estimated final electricity price for large industrial customers in energy-intensive industries: USA 50 USD/MWh China 68 USD/MWh https://www.iea.org/reports/electricity-2026/prices https://www.iea.org/reports/electricity-2026/prices
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- tokai 2mo agoI don't know, non of the chinese models I use are served from China. And they are still cheap.
- preommr 2mo agoI thought the chinese models were cheaper per token, but about the same or more expensive on tasks because they used more tokens for reasoning. Cutting even further, seems like a really big leap.
- simonw 2mo ago> The kernel work helped reduce the end-to-end cost of serving the model by 20%, while its experiments increased token-generation efficiency by more than 15%. If the cost of serving GPT-5.6 just dropped by 20%, does that add up to literally billions of dollars in savings per month? We know Anthropic spend $1.25 billion renting inference capacity from SpaceX (in two Colossus datacenters) from the SpaceX IPO, but we don't know how much of Anthropic's inference capacity that is (presumably a small fraction, since they were operating on top of AWS and other providers before the SpaceX deal.) I've not seen any numbers that hint at OpenAI's per-month inference bill, but surely that has to be in the multiple billions of dollars as well. So 20% is a really, really big deal.
- dominotw 2mo agoimagine writing that on your resume > reduced inference cost by 20 percent saving company x billion dollars per month
- tekacs 2mo agoIn this case, and I don't mean this critically, I guess it would technically be, "Instructed model to find efficiencies... reducing inference cost by 20% saving company x billion dollars per month." I have no doubt that further work was required to enable this, but it's still very cool to be possible to say that.
- da_grift_shift 2mo agoDoes the model get the credit for its promo packet then? :^)
- andai 2mo agoI think they meant that GPT-5.6-Sol can write that on its resume.
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- pavpanchekha 2mo agoMaking Luna, which was already very cheap and extremely capable, 5x cheaper is crazy. I use Sol at work but Luna at home, and while there's definitely a difference, it doesn't feel like night-and-day. After a year of ever-increasing prices it suddenly feels (between this, Kimi K3, GLM 5.2) that prices are falling again.
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- jedberg 2mo ago> Sol vs Luna > it doesn't feel like night-and-day. I see what you did there. :)
- deklesen 2mo agoGood observation! Kudos
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- dominotw 2mo agodepends on what you are doing. if you are doing verifiable tasks like fixing bugs then any model would do as long as you write the right verification.
- maxdo 2mo agois kimi that cheap? it's a very expensive model
- pixelesque 2mo agoIt's cheaper currently on many of the inference providers. Personally, I'm having surprisingly good results with DeepSeek 4 Pro at home, which is very good value for money: it's not as good as Claude / GPT 5.6 (I have Co-pilot license at work), but it's still really useful for code reviews, validating thoughts, and especially designing / writing unit tests for new (and old before refactoring) functionality. And it's very cheap per task. (Flash is even cheaper, but I've had issues with that on more complex tasks where it starts forgetting things and arguing with itself "but wait, let me read the function again").
- measurablefunc 2mo agoModel segmentation & distillation like this that asks the consumers to pick exactly which version of the algorithm will solve their problem is evidence for lack of intelligence instead of its presence.
- dominotw 2mo agoit is really hard to know upfront if you have fuzzy task. sometimes i would choose a cheaper model and it will spin and spin with bad outputs ending up costing more had i chosen a more capable model.
- cute_boi 2mo agothere is mixture of experts which is also another routing. So, simple change in prompt can be a big difference.
- beering 2mo agoYou really really don’t need to pick. Just use Sol on high. That’s my daily driver and I don’t touch the model picker at all. Now, if cost is your concern, then that’s a problem in all of computing. Hence why I’m sending you short plain text messages using an iPhone with a many-core CPU and gigabytes of RAM.
- measurablefunc 2mo agoThat's great. I'm sure you get a lot of good value out of it but eventually OpenAI will have to become profitable & they might curtail consumer resources.
- sidcool 2mo agoThey don't mention Grok at all.
- andybak 2mo agoDon Draper in the elevator meme?
- hirako2000 2mo agoOf course. All comparison is with what makes them look good.
- wilg 2mo agoWhat would they say about Grok?
- infinite_spin 2mo agoHang on, I need to create a Twitter account so I can ask Grok
- paxys 2mo agoThey also don’t mention a hundred other models.
- qingcharles 2mo agoMusk announced Grok 4.6 coming next week, no idea what changes that brings or how it compares to the current 4.5.
- goldsmith112 2mo agoNot sure who would use Terra anymore. Pair Luna High/Xhigh with Sol Medium and that's your power stack
- fritzo 2mo agoSounds reasonable. Is there a good benchmark on which make this decision?
- espadrine 2mo agoI maintain this meta-benchmark leaderboard: https://metabench.organisons.com/ https://metabench.organisons.com/ With this new price change, Terra does look pretty Pareto’ed by Luna. On agentic coding, pairing Sol Medium for architecting with Luna High for coding does kinda make sense. But beware that architecting can be very read-heavy, and Sol is a bit read-pricey compared to Terra.
- Argonaut998 2mo agoThanks, I was looking for something like that
- andai 2mo agoSol as main agent, Luna for coding?
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- swingboy 2mo agoThis is awesome. Luna is a pretty great model on xhigh.
- preommr 2mo ago> Starting today, GPT‑5.6 Luna, our fastest and most affordable model, will cost 80% less, I don't have the words. I genuinely thought we were in a stage where we were plateauing and going in for 5-10% improvements over months. Seeing spikes like this makes me question about where the floor really is.
- buckle8017 2mo agoThey over purchased hardware. This is very likely priced below recovering the cost of the hardware but still above operating expenses.
- infecto 2mo agoWhat evidence is there? I have no idea either way but one thing that detracts from these threads is folks claiming things as a fact without evidence.
- qntmfred 2mo agosama literally just said they wish they had bought more. the price drops are almost certainly due to good old fashioned hardware innovation (wafer scale with cerebras) and optimizing hardware development based on model architecture and inference costs. other inference providers will try to do the same if they can. https://www.youtube.com/watch?v=XDB5beon4DY&t=4m20s https://www.youtube.com/watch?v=XDB5beon4DY&t=4m20s
- paxys 2mo agoThat’s ridiculous. Every major AI lab is compute constrained. That’s exactly why nvidia is worth trillions today. If OpenAI had a single extra GPU they’d be using it to run another training cycle or experiment for their next model.
- captainbland 2mo agoTo be fair we don't really know in terms of prices what's real and what's just investor subsidised attempts at market capture at this point. It could well be OpenAI's attempt to drown Anthropic while they've got the halo product if they feel they've got deeper pockets.
- gentlewater 2mo agoThis is awesome. I’ve recently set up my opencode to use 5.6 terra for my main agent, who delegates work to a 5.6 Luna coder agent. So far it seems to work well, and reduce costs a lot. With this price reduction, it will work a whole lot better. Perhaps I can get my github copilot quota to last the whole month now.
- tosh 2mo ago80% price cut for luna is a very aggressive pricing move makes it by far the best choice for most workloads that do not need bleeding edge intelligence (reminder: luna can be comparable to opus 5!)
- heaney-555 2mo agoLuna is meant to compete with Haiku. What tasks are you seeing it equal Opus on?
- tosh 2mo agoluna is way better than haiku 4.5
- nateb2022 2mo agoI use Luna a lot (over 1T tokens since it came out) and I'd rank Luna (high/xhigh) on par with Sonnet 5, without hesitation.
- euazOn 2mo agoPer Artificial Analysis: - Haiku: 30 points - Luna Medium/High/Xhigh/Max: 38/46/49/51 points That's a massive difference: - 30 points is Gemma 4 31B territory - 50 points is GLM-5.2 (744B) territory.
- ignoramous 2mo agoCould OpenAI be running a different model for high+max?
- wahnfrieden 2mo agoNo OAI is just very good at reasoning models
- newtwilly 2mo agoAccording to the Artificial Analysis benchmark graph in the article, Luna can now outperform Sonnet 5 and Opus 5 low at ~4-10x less cost
- firasd 2mo agoThis is one of the things OpenAI has been focused on for an year or so that led to the doomed autoswitcher in ChatGPT .com (switching models based on estimated task complexity) that was quickly reverted Whereas Google with Gemini 3.x, Anthropic with Fable etc are happy to just go for 'big model with dense params' It's hard to guess from the outside of course but just this kind of talking points focus on GPU efficacy is what we see from OpenAI and Chinese open source labs more often than from Anthropic or Google Deepmind and this benchmark chart seems to concur
- welcomezhangjun 2mo ago[flagged]
- bob1029 2mo agoThis feels like the dialup->broadband transition to me. I was already a huge proponent of Luna for things like deep research. Being able to run 5x more for the same cost is simply bananas. We are already running 10 parallel agents for hypothesis generation. I cannot imagine 50. The statistics become much more interesting & powerful when you can run so many samples of the exact same prompt+model without breaking the bank.
- andai 2mo agoDo you have a sense of which tasks benefit from more agents and which don't?
- bob1029 2mo agoAnything related to reading and interpreting the environment seems to always benefit from the addition of more agents to the search party, assuming you have some rational way to synthesize their results. Taking actions that mutate the environment is a different story. I think this is where you run into diminishing returns very quickly. You generally want one strong agent to act given the results of all the searching that was done. If the plan is clear, you don't need a genius model to execute it.
- handfuloflight 2mo agoI definitely think you want the genius model to synthesize everything that rolls up to them.
- kridsdale1 2mo agoThis is why in your brain you have trillion threads processing and summarizing sensor data (immutable functions), but a SINGLE thread of “execution” which we call the conscious soul.
- andai 2mo agoI think this is an unsolved problem. The most interesting thing I saw here is the Recursive Language Models paper. https://arxiv.org/abs/2512.24601 https://arxiv.org/abs/2512.24601 There's also a great write up here by the author: https://alexzhang13.github.io/blog/2025/rlm/ https://alexzhang13.github.io/blog/2025/rlm/
- dannyw 2mo ago[dead]
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- alvis 2mo agoBasically lunar at extra level can cover all use cases scenarios other than those requiring opus up. Goodbye sonnet and haiku
- sosodev 2mo agoLooks like I might have a reason to use something other than Deepseek V4 Flash.
- andai 2mo agoI was curious so I photoshopped DSV4 Flash into the graph: https://files.catbox.moe/csxl32.png https://files.catbox.moe/csxl32.png (2 cents to run AA index, score 40) Looks like OpenAI broke the pareto frontier on the trust-me-bro benchmarks! (One has to wonder if they used any of the neat tricks from the DSV4 paper :)
- GodelNumbering 2mo ago"Half the money I spend on advertising is wasted; the trouble is I don't know which half." -John Wanamaker This applies even more strongly to model choosing. I know for a fact that majority of my work doesn't require a very strong model, but separating the trivial and non-trivial tasks is a famously hard problem (if at all decidable).
- fractorial 2mo agoCosmically apt username given the substance of this comment.
- hellojimbo 2mo ago[dead]
- throw2ih020 2mo ago> separating the trivial and non-trivial tasks is a famously hard problem (if at all decidable). Famously, this is also a problem for human coders in sprint planning.
- carimura 2mo agoExactly. I haven't reached the "let 1000 agents bloom" mode yet, so currently I'm spending real headspace managing agents doing work, and that work is all important, so why "settle" for sub-frontier models for that work? Maybe I'll get there for non-coding work.
- odiroot 2mo agoYou just need a very strong frontier model to do triage of your tasks. /s
- quirino 2mo agoI generally just check the Price/Performance graph on Openrouter: https://openrouter.ai/rankings#performance#benchmarks https://openrouter.ai/rankings#performance#benchmarks. Activate the "Show Pareto" toggle on the right. I was still using GLM-5.2 in my personal projects, but this just made Luna a very easy choice.
- hattimaTim 2mo agoThe official doc says, Luna = Previous Nano models, kind of. Is it really good at coding?
- paxys 2mo agoSmaller models are great if you are doing targeted changes in existing codebases. Don’t expect to use it for creating complex architecture from scratch or do major refactors. The larger the context, the greater the drop off will be.
- dannyw 2mo agoSmaller models are also excellent executors/operators. When given a solid plan, including e.g. what files/functions to change and how, what to test, even a recent 27-30B open weight model will usually do an excellent job.
- quirino 2mo agoAccording to the link I mentioned above it's roughly as good as GPT-5.4. Haven't tried it in practice yet. I bet it must be better in some contexts and worse in others.
- PhilippGille 2mo agoDepends on the reasoning effort, see https://deepswe.datacurve.ai https://deepswe.datacurve.ai (add Luna via model selection drop down, if it's not shown by default)
- 2mo ago
- wronex 2mo agoWhat are your use case for these? I’m manly interested in coding where more capability is better - give me a 10x model at 10x the price and I’ll take it. A worse model at very low cost has no appeal to me. At-least not for coding. Translation maybe? OCR?
- stri8ted 2mo agoTranslation, moderation, classification, guardrails, etc..
- Yopolo 2mo agoAgentic layer. Your support bot. Your research long running bot. Your SEO Optimizer bot. Your incident analyser bot. Your personal assistent bot.
- wronex 2mo agoGame play bots (monsters, commanders maybe) would be really cool. But it needs long term support and probably local AI instead.
- Yopolo 2mo agoYeah great point. 2 years ago i wouldn't have thought that this is even feasable but today? Lets start of with 1000 ai credits which should be enough for one playthrough, have it included into the game.
- therealdrag0 2mo agoDinky stuff I want to be fast like “update the PR with this other JIRA ticket”
- shepherdjerred 2mo agoSummarization of datasets, categorization
- dannyw 2mo agoGeneral light/defined tasks, e.g. go fetch a list of rows from <X> and then run script <Y> against each. Yes, I can just do it myself, but even at API prices, I'd rather have the LLM do it.
- kingstnap 2mo agoThose prices on luna are killer. Haiku was already in a ditch. But this is coming straight for the jugular of a ton of models on openrouter.
- fractorial 2mo agoIt would appear that rolling my own Anthropic-free harness / serving stack with a closed-weight carve out for Codex models is an absolute win.
- peheje 2mo agoMight just resub. Will experiment with Luna next sessions. 5 h window is not working very well for me. But if I can drop down to Luna at 20-30 % left and comfortably ride out the wave then.. that might just work.
- arcanemachiner 2mo agoThey got rid of the 5hr quota, it's just weekly quotas now.
- gck1 2mo agoThey're supposed to bring 5h today.
- __jl__ 2mo agoDidn't expect that. Luna pricing is crazy now. I don't think there is anything on the market that competes at this price-performance point. For our production app, OpenAI clearly is the best provider now. Their API is very reliable and has many nice features. The price-performance of the model lineup is incredible. We used open weights model via Fireworks for a long time (e.g. Kimi K2.5). Fireworks is a great provider but we still ran into issues here and there (Same with Anthropic and Google). OpenAI just works, is fast and in my view has a better price-performance ratio across almost all levels of intelligence.
- dannyw 2mo agoOpenAI's APIs are extremely reliable for sure. I don't even remember when the last incident or downtime was.
- amluto 2mo agoThis doesn’t quite count as “API”, but OpenAI’s roll out of OAuth device code authentication was poor, to say the least.
- jofzar 2mo agoWasn't it down last weekend?
- sipjca 2mo agoall day yesterday, Taiwan time Sol was having significant issues. “Overloaded”, maybe half of requests or more wouldn’t go through
- Rendak 2mo agoThat’s what I was seeing too, and my cache hit rate was below 25% during that same time, leading to significant burn of my weekly limit (Pro 5x plan) via all the uncached input. Doesn’t prove that the overload caused the cache failure, but it does seem to point to some common infrastructure cause. No such problems (cache hit or system overload) with Terra or Luna.
- jnakano89 2mo agoSeems like they cut the tiers(GPT-5.6 Luna) where GLM and Kimi compete and still held margin for their frontier models
- ninjahawk1 2mo ago80% less for Luna is absolutely crazy, in my opinion we may reach a point in the next year where powerful models on the API could potentially be cheaper than subscriptions. Compute just keeps decreasing in price.
- HDThoreaun 2mo agoAPI will never be cheaper than subs because theres a ton of value created for companies by locking people into subscriptions that tend to be sticky.
- andai 2mo agoIt says Luna is fastest, but doesn't it take way more steps to get the same job done? https://deepswe.datacurve.ai/ https://deepswe.datacurve.ai/ - (See the Agent Steps view) Or is the output speed so much higher that it cancels out? I don't see a lot of benchmarks that record actual time. But on AA, Sol on Low beats Luna on High for Time Per Task.
- paxys 2mo agoThe type of job matters. If it is too complex then yeah, you should be using a larger model.
- incognito124 2mo agoWhile I can't deny this is a huge technological result, and it's laudable they reduced the price because of it, 80% is really a lot. I can't help but wonder, is this because of the model's capabilities, or was the initial system just really sloppy? The public will probably never know the details
- baalimago 2mo agoWe swapped an internal system from gpt-5-mini to gpt-5.6-luna and saw no benefit but 4x cost. Sufficed to say: we swapped back to gpt-5-mini.
- gbnwl 2mo agoExperienced similar between 5.4-mini vs 5.6-luna in our own pipelines but after spending some time on prompt optimization and testing out various reasoning effort levels 5.6-luna was well worth it. Did you just replace model selection while keeping everything else in place or spend some time on evaling with newer prompts etc?
- baalimago 2mo agoNo we kept prompts as is, just swapped model. The prompt is already quite optimized for the task. How would updating it possibly make a more intelligent model spend less tokens than a less intelligent model? Care to elaborate?
- Tankenstein 2mo agoMost of the time when upgrading models we have needed to change prompts to get the same performance (let alone better performance). Usually, your prompt is overfit to the specific model doing the specific task. For example often your previous prompt is overspecifying and creating contradictions that a dumber model would just gloss over whereas a smarter model will try even harder to follow.
- steveklabnik 2mo agoHere is an example of a guide from OpenAI on how you should prompt 5.6 differently than their previous models. https://developers.openai.com/api/docs/guides/latest-model#prompting-best-practices https://developers.openai.com/api/docs/guides/latest-model#p...
- gbnwl 2mo agoI think the fundamental difference between our assumptions is you believe prompts to be optimized for tasks rather than model-task pairs. The only elaboration I can give you is empirical observations and model providers own guidance (as someone has already linked here). I'm pretty sure you probably have specific parts of your prompts that came about due to specific failure modes observed in your evals of running the task against first model. These vary across models in my experience, and it's always worth redoing this calibration process.
- purpleidea 2mo agoI would pay significantly more to use these models if there was a legal contract that guaranteed they weren't ever terfing them and some way to prove that.
- StilesCrisis 2mo agoWhat?
- thehamkercat 2mo agonerfing*
- weird-eye-issue 2mo agoDon't you realize how many people are using these in production and rely on responses in very specific formats and have logging and metrics in place to detect any issues and if they were just randomly nerfing models they would cause major issues in production that tons of people would immediately notice? The easy way to prove this is to set up your own evals and then run them daily
- conception 2mo agohttps://marginlab.ai/trackers/claude-code/ https://marginlab.ai/trackers/claude-code/ Has been pretty accurate when pre-release quality or bugs pop up. In theory you could run your own.
- hadlock 2mo agoSeems like they're working to destroy the local LLM argument. Right now Haiku is $1/$5 in/out. You can grind out $12,000 worth of haiku (or arguably, sonnet) class tokens in about 5 months on a Blackwell RTX 6000 96GB especially if using concurrency. BUT, but, if you use a g6e.xlarge on aws it's now more expensive than buying tokens from OpenAI @ $0.20/$1.20. It also destroys "the Mac Mini argument", pushing the ROI to ~4 years.
- jrflo 2mo agoThe local LLM argument never really held water tbh. You can get surprisingly good performance for lightweight tasks locally, but you're just fighting economies of scale if you're going trying to beat a datacenter on cost.
- simianwords 2mo agoLocal LLM argument was always ideology first and never ever about economics.
- hadlock 2mo agoI just gave you the ROI on a retail blackwell card, the math checks out, particularly on overpriced Haiku and Sonnet, what do you mean by "you're just fighting economies of scale if you're going trying to beat a datacenter on cost" ?
- efficax 2mo ago"too cheap to meter" and Luna is still more expensive than deepseek-v4 pro
- jrflo 2mo agoIt's marketing hyperbole, but Luna is more intelligent per dollar than deepseek-v4 pro. Cost means nothing without the associated capability
- efficax 2mo agois it? i don't know how we measure these things, but here's one measurement that says v4 pro is better than luna: https://artificialanalysis.ai/models/comparisons/gpt-5-6-luna-medium-vs-deepseek-v4-pro https://artificialanalysis.ai/models/comparisons/gpt-5-6-lun... presumably it's a much bigger model
- lightinglabs 2mo ago[dead]
- NortySpock 2mo ago> In a compute-constrained world where model demand is growing faster than capacity I don't buy it. There have been recent weeks where some of the mid-level models (Hy3, Laguna M.1) are free (true for parts of June and July, see Hy3 in Cyan) . Even then the total token usage appears to be reaching a steady-state. https://openrouter.ai/rankings#top-models https://openrouter.ai/rankings#top-models ^ the first graph is tokens per week across all models I guess we just can only throw ideas at an LLM at a certain rate. I still have ideas and now I can have an LLM vibe code what I want, but I'm not going to let an agent just run unattended for longer than a few minutes or a few bucks for hobby projects. So maybe it is a matter of lowering the cost of an LLM so I can let it churn for hours at a cost of pennies... But I suspect demand for tokens is very price-elastic.
- Yopolo 2mo agoThese are free due to some different type of reasons like Nvidida sponsoring free tokens or the model companies. My company checks the models and pays for Opus through AWS. You still send the WHOLE context of whatever you want to do to a random endpoint on the internet. If you want to write a good email, you give that context your email address, names, the reason for it etc. Big companies don't randomly use some random api endpoint to do so. Anthropics quarerly revenue is still growing very fast. I don't think we have seen even the real potenzial of it yet at all. Not only are still a lot of countries missing which do not even use anthropic or any other frontier model yet but also all the agentic based solutions enterprise companies are currently building on mass (at least in my industry)
- Der_Einzige 2mo agoOpenrouter is not even CLOSE to the majority of tokens. I don't know where this myth came from that they account for even ~5% of total token spend! It's not true!!!! Stop rejecting what we have been collectively telling you guys! LLM providers are profitable, and have been for awhile!
- Aboutplants 2mo agoYour move, Anthropic
- arjunchint 2mo agoDeepseek Flash is still much cheaper: - lower input/output token pricing - the cached token price is $0.0028/Million tokens, which is like 50-90% of tokens
- msejas 2mo agoIsn't OpenAI burning billions and have billions more spending commitments? If they managed to downsize so much the cost they should have kept the price the same and become profitable, really weird move, unsure what led to this.
- paxys 2mo agoSupply demand curve is a thing. Cutting price on something does not mean you are going to make less money.
- dgellow 2mo agoBut they still have to cover compute cost, and they already committed to more than $650B in infra expenses for 2035
- dgellow 2mo agoMore than $650B due 2030. I don’t understand how it makes any sense that they reduce the price so much, unless they expect seriously such a massive saving and increase in demand from their latest improvements?
- otherme123 2mo agoSlower grow, or even shrink in usage? Right now, the promise of a future "everyone will use our models and pay whatever we ask" is what keeps $$ flowing towards OpenAI.
- shevy-java 2mo agoThe milking games have started. The billionaires want their money back. Edit: Yes, 80% minus is still milking. Because you empower these greedy mega-corporations. Just look at the RAM prices increase, then you see that the more money you give these hungry dragons, they more they will eat up. Don't get fooled by their "less cost now" advertisement.
- Phlogi 2mo agoIt's a clever strategic move: grab the market of cheap low end models within the product range. It's lower friction to switch a model than a provider.
- Decabytes 2mo agoHas anyone ever done a comparison between the smaller models like Luna, against the previous GPT 5 frontier models? Have we gotten to the point where the small models are as good as the frontier models of the past, or is there still a way to go?
- simianwords 2mo agoI ran a prompt with ChatGPT since I'm also curious. The price reduction is crazy. - GPT-5 high: score 35, approximately $0.37/task - Luna medium: score 38, approximately $0.01/task - Luna max: score 51, approximately $0.042/task So Luna medium is: - slightly more capable than GPT-5 high; - approximately 35–40× cheaper per benchmark task. And Luna max is: - 16 Intelligence Index points better; - still roughly 9× cheaper per task. This reduction was possible within 1 year.
- Pesto 2mo agoI truly wonder what kind of model is luna now. Before I thought it was just an improved version or at least in the same class as gpt 5.4 mini but now it's being priced like a nano model! I thought about it because Terra has similar pricing to 5.4 and Sol is similar to 5.5. Luna was already my workhorse before, it performs very well on high/xhigh for most of the tasks, very happy about this drop.
- hugopuybareau 2mo ago> These lower prices for Luna and Terra are also reflected in how usage is counted against paid subscriptions Does this seem higher or lower limits ?
- guybedo 2mo agogpt 5.6 luna was already at the intelligence/cost frontier and it's now even cheaper ...
- simianwords 2mo agoThere were people on HN who still thought that the API prices were being subsidised. The level of conspiracy theory was off the charts on this topic. You would get these price reductions month over month you would still have people believing in crazy stuff.
- amazingamazing 2mo agoLink to definitive price info?
- weird-eye-issue 2mo agoI mean to be fair this price reduction does not prove anything If somebody already thought the price was subsidized then this price change would just mean it's even more subsidized, so why would that change their mind?
- archon1410 2mo agoIf Luna is so good and cheap, I'm wondering why ChatGPT Free users still only have access to GPT 5.5 Instant. The API pricing for chat-latest is the same as Sol(!),[1] while Luna is 25× cheaper [2]. Even assuming highly inflated API pricing for chat-latest, Luna not being the daily driver on Free and Go plans feels off. Perhaps users prefer instant responses over thinking models so much so that using a more expensive and less performant non-thinking model is worthwhile. [1] https://developers.openai.com/api/docs/models/chat-latest https://developers.openai.com/api/docs/models/chat-latest [2] https://developers.openai.com/api/docs/models/gpt-5.6-luna https://developers.openai.com/api/docs/models/gpt-5.6-luna
- randomblock1 2mo agoI bet they'll switch over pretty soon. They always make free users use the older models for a little bit, probably to try to push people to upgrade. You can actually use Luna without reasoning (set it to "none"). So if they wanted to, they could definitely replace 5.5 Instant with it.
- archon1410 2mo agoGood points. Though GPT 5.5 Instant does beat out 5.6 Luna non-thinking 34 to 27 on Artificial Analysis Intelligence Index.[1][2] This could mean it is optimised for non-reasoning perfomance. So even if beaten on cost and performance, it could still be on the pareto frontier for speed. It probably costs them a substantial amount of money everyday to not replace Instant with Luna, and the people who want larger models will upgrade regardless of whether they get Instant or Luna on the free tier. It is unlikely the amount of people upgrading just to have latest models would be enough to offset the costs. [1]https://artificialanalysis.ai/models/gpt-5-6-luna-non-reasoning https://artificialanalysis.ai/models/gpt-5-6-luna-non-reason... [2]https://artificialanalysis.ai/models/gpt-5-5-instant-05-26 https://artificialanalysis.ai/models/gpt-5-5-instant-05-26
- pbowyer 2mo agoFriendly reminder that GPT-5.6 in Codex cannot spawn Luna subagents, only Terra [1] To fix this you currently need to make your own copy of the bundled model catalog [2] and opt Luna into MultiAgent V2. 1. https://github.com/openai/codex/issues/32031 https://github.com/openai/codex/issues/32031 2. https://github.com/openai/codex/issues/32031#issuecomment-5111515732 https://github.com/openai/codex/issues/32031#issuecomment-51...
- wahnfrieden 2mo agoI don’t understand why they keep this broken
- mark_l_watson 2mo agoI prepaid for a ton of DeepSeek v4 flash tokens. When I use them I would like to try purchasing Luna tokens for a while. I like cheap and fast models and since I am retired, if I waste time having to sometimes manually switch to a stronger model, that is OK with me.
- wxw 2mo ago> $0.20 per million input tokens and $1.20 per million output tokens for Luna This is... ridiculously cheap. Amazing!
- infinite_spin 2mo agoI've been having issues with it using unreasonable timeouts for tasks that should have failed within minutes, not hours.
- redrix 2mo agoTo save people a click (output price per 1M tokens): GPT 5.6 Luna: Was $6.00. Now $1.20 GPT 5.6 Terra: Was $15.00. Now $12.00. (edit: formatting)
- redrix 2mo agoCompetition is a wonderful thing. $1.20 per 1M output is crazy, but let’s also not forget that OpenAI was one of the first to start increasing model prices ~10-12 months ago. GPT-5 cost $10 (per 1M output) They still have to pay back those hundreds of billions of investment dollars somehow. The best thing any developer can do today is to make their app LLM/provider agnostic (or use an LLM gateway) to avoid lock-in.
- polishdude20 2mo agoTried Luna on a bunch of pdf extraction tasks with data tables. Seems to consistently miss table rows a lot.
- wahnfrieden 2mo agoLuna on what reasoning level. Try Max
- linzhangrun 2mo agoDeepSeek may suffer from this... The official version has still not arrived, and Luna now costs only 70% of V4 Pro. Just imagine how much the same level of intelligence cost only a few months ago.
- kzrdude 2mo agoDS V4 flash has been updated today! https://api-docs.deepseek.com/updates/ https://api-docs.deepseek.com/updates/ The update seems to say that it's a re-post train of exactly the same model.
- smusamashah 2mo agoI wish Sonnet 4.6 gets the similar low pricing. It is also a very good model and I can keep using it forever. It would be more awesome if it is burned on the Taalas chip.
- jartan2002 2mo ago[flagged]
- vinhnx 2mo agoGPT-5.6 Luna xhigh/max from Codex is my daily driver now. Good economics, good performance. It sits in the most attractive quadrant on the Intelligence Index.
- armanj 2mo agoany particular reason not using terra or sol, given the generous limit quotas and frequent codex resets?
- wahnfrieden 2mo agoI run out of my 20x account with Sol medium and some Sol high in about 2 days
- vinhnx 2mo agoBecause Luna feels right and just enough for me.
- armanj 2mo agomight as well rethink about their pricing on gpt-realtime. for a quick test, spoke to that model for ~5 minutes, ended up spending near $1.
- wahnfrieden 2mo agoThey haven’t launched the new realtime in api yet
- armanj 2mo agohttps://developers.openai.com/api/docs/models/gpt-realtime-2.1 https://developers.openai.com/api/docs/models/gpt-realtime-2...
- WhereIsTheTruth 2mo agoThe US just undercut China, i repeat, the US just undercut China What a time to be alive, the fall of the Chinese edge
- XCSme 2mo agoI think that with this change, DeepSeek v4 Flash has finally been dethroned.
- XCSme 2mo agoOr maybe not: https://news.ycombinator.com/item?id=49119559 https://news.ycombinator.com/item?id=49119559
- feiz45607 2mo ago[flagged]
- unknown2342 2mo agoAll the AI Mambo jumbo and still the Y axis is written from down to top. I hate that.
- rldjbpin 2mo agolet's not forget the forest for the trees. the new pricing is more aligned with their previous generation of similar models. case in point 5.4-nano, which is the only model of its class which is now finally comparable to 5.6-luna in pricing. [1] until this change, workflows using the older model could not economically justify the old luna pricing. the doubling in price between 5.4 and 5.5 also did not help with things, but now 5.6-terra can be considered an update for this pricing tier. if the token efficiency is real (which i am yet to replicate for our workflows), then the switch to these models can be a net benefit. thank you chinese labs! [1] https://developers.openai.com/api/docs/pricing#text-tokens https://developers.openai.com/api/docs/pricing#text-tokens
- troglodytetrain 2mo agoSo, no offense but DeepSeek and other Chinese providers are the ones actually advancing the price-perf here. Being less expensive than Anthropic isn't impressive.
- 8801729-829863 2mo agor34tfWsUexi7