| ▲ | simonw a day ago |
| 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. |
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| ▲ | gizmodo59 a day ago | parent | next [-] |
| 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. |
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| ▲ | sieve a day ago | parent | next [-] | | My OpenCode Go stats for the last 30d: Cached Read: ~6,500M Input: ~150M Output: ~20M Approx $40 worth of usage across DeepSeek V4 Flash + MuseSpark Contributor 1.3. And a bit of both the GLM models. This is covered in a $10 subscription. If I were to use Luna's API pricing: $0.02 x 6,500 = $130 $0.20 x 150 = $30 $1.20 x 20 = $24 So $184. And this is assuming smaller coding sessions (<272K) beyond which Luna pricing doubles. -- Cost wise, these models are nice for small stuff. Translations etc. Any model that does not provide multiple Mtoks of cached reads per cent is not very useful to me for coding workflows. | | |
| ▲ | nearbuy a day ago | parent | next [-] | | This isn't right. You're comparing cost per token, but DeepSeek V4 Flash uses more tokens. Artificial Analysis found GPT 6 Luna to be significantly cheaper than DeepSeek: https://artificialanalysis.ai/models/comparisons?compare=dee... | | |
| ▲ | sieve a day ago | parent | next [-] | | I do not (generally) trust benchmarks. I only trust what a model does with MY code. Forget DS. I asked MiMo 2.6 yesterday to explain ML/LLMs to me succinctly and the pointed it at Karpathy's micrograd code. It produced a C implementation called `xor_mlp`, a tiny model that learnt how `xor` worked. I then asked it to produce a model that can play tictactoe without losing (mostly). It did. It supervised the training process and produced a compiled version with multiple switches. The pi-dev session is still running, so here are actual stats ↑45k ↓35k R1.0M CH99.4% $0.019 4.2%/1.0M (auto) - (opencode-go) mimo-v2.6-flash • high And here is Luna on the same workflow (I had to poke and prod a bit to get what I wanted): ↑141 ↓34k R1.0M W43k CH95.3% $0.072 4.2%/1.1M (auto) (opencode-go) gpt-5.6-luna • high I expect similar results from DS41F/MS13. Closer to MiMo costs than Luna. So the "significantly cheaper" thing may not really hold, more so when Luna has to actually read my codebase to do the stuff that I want rather than rely on world knowledge. The 8-10x cache read cost differential itself will kill the token budget. | | |
| ▲ | nearbuy 17 hours ago | parent | next [-] | | With GPT-6 Luna (which is what the parent comment was talking about), that would come to 3.2¢, assuming GPT-6 used the same number of tokens. I don't think you can guess more precisely than an order of magnitude from trying each once on one task. | | |
| ▲ | sieve 16 hours ago | parent [-] | | DS is VERY talkative. Luna is less so. Still do not think, based on this little experiment, that Luna could beat DS in price: API-to-API. As part of a Plus/Pro plan? Sure. | | |
| ▲ | ducktoysleftout 7 hours ago | parent | next [-] | | Its style of writing is part of the fun. Seeing reasoning traces fly by that each start with “Hmm…” is pretty amusing in my opinion especially if you try to vocalize it in your mind. | | |
| ▲ | Thanemate 6 hours ago | parent [-] | | In a discussion about cost effectiveness, how subjectively fun the writing feels like to the reader isn't a factor, except maybe if we were working on writing comedy. |
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| ▲ | yunohn 4 hours ago | parent | prev [-] | | Well, DS shows the thinking stream so it feels that way, but I’ve realized that OpenAI hiding it just gives a false impression - the non thinking output is also very wordy for OpenAI models. |
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| ▲ | asaddhamani 18 hours ago | parent | prev [-] | | Don’t know if it’s still true but with Chinese models, using Western API providers is significantly more expensive and using Chinese providers they will train on your inputs without exception. That has kept me from using these ultra cheap endpoints. | | |
| ▲ | asp_hornet 17 hours ago | parent | next [-] | | > without exception Is this based on something or just because “they’re Chinese and they’ll do anything to win”. | | |
| ▲ | asaddhamani 16 hours ago | parent | next [-] | | This is based on my last check of alibaba and Deepseek TOS. If the Chinese will do anything to win, so will the Americans. I’m not American or Chinese and I have no reason to trust either side. I do think Chinese models are better price performance and actually open which is in many cases better. | |
| ▲ | r_lee 13 hours ago | parent | prev | next [-] | | it's very well known Deepseek does it, their whole discounted pricing was seemingly priced on that. you can't even use Alibaba on Openrouter if you enforce ZDR | |
| ▲ | someguynamedq 16 hours ago | parent | prev [-] | | Why on gods green earth would they not if they can? |
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| ▲ | sieve 18 hours ago | parent | prev [-] | | Do you really think Western providers will not train on your data? I have no such illusions. I try to keep PII out of what I share with LLMs. Otherwise, I do not see the point, really. Very little of my code is "unique." I simply approach things a bit differently. Otherwise the algorithms and code would be similar to what others with domain knowledge would write. So much of code and algorithm implementations are available in the open. And LLMs have trained on all of them. What they most probably gain from you is your prompts and your thinking approach more than the code. | | |
| ▲ | ascorbic 16 hours ago | parent | next [-] | | The US labs would lose billions in enterprise contracts if they were found to be secretly training on data when opted-out. It's not worth it. | | |
| ▲ | dhx 14 hours ago | parent | next [-] | | Great in theory, but what are US enterprises going to do _if_ their private data is later found to be used for training? 1. Not use AI technology and fall behind the rest of the world. 2. Use Chinese AI technology, either hosted by Chinese companies or the models self-hosted. 3. Sue US AI companies for damages, but not enough to have any meaningful impact to such companies that it'd impact US national security goals (per US government contribution to NY Times copyright lawsuit). | | |
| ▲ | vikramkr 5 hours ago | parent | next [-] | | 3. They would sue. And it could have very meaningful impact. NYTimes copyright lawsuit is not a valid comparison because because that's a violation of national/state law which really only matters to the extent that the government is enforcing that stuff which is not the biggest concern rn (these companies are large enough that the threat of the legal costs of fighting in court is not that scary and you'd need a government actually willing to punish them substantially for them to be scared). This stuff would be under contract law against other mega corporations with big legal teams who are also their customers which is a much scarier prospect imo | |
| ▲ | Kyo91 12 hours ago | parent | prev | next [-] | | There's a huge difference between AI companies exploiting a grey area like training on public corpora and violating a private contract that they explicitly entered into with another party. The latter is very explicitly illegal and would never survive trial in Delaware Chancery court. And all of that is before we get into Federal contracts where training on TS/SCI data could lead to criminal charges. There's a huge market in the US for providing AI services while respecting client privacy. It makes sense for at least one major provider to offer this. | |
| ▲ | heon29 11 hours ago | parent | prev | next [-] | | > Great in theory, but what are US enterprises going to do _if_ their private data is later found to be used for training? This. And it’s already happening: > 2. Use Chinese AI technology, either hosted by Chinese companies or the models self-hosted. | |
| ▲ | tomnipotent 7 hours ago | parent | prev [-] | | > Sue US AI companies for damages Yes that's the whole point, at least it's an option in the US and Europe. Good luck getting any redress from China. Anthropic was already hit with a $1.5B class-action which would be impossible against a Chinese business. |
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| ▲ | atmosx 13 hours ago | parent | prev [-] | | Oh. Yeah of course… and the US population will revolt if the figure the NSA is spying on them. |
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| ▲ | asaddhamani 16 hours ago | parent | prev | next [-] | | People use LLMs for far more personal tasks than just writing code. There are AI journaling apps for instance. And yeah, western providers give you a toggle but I don’t know if that toggle actually does anything or not. They were fine with collecting training data in many morally questionable ways before, no reason for them to stop when you’re literally handing it over to them. | |
| ▲ | intended 16 hours ago | parent | prev [-] | | The meager difference is that, in theory, you can eventually sue people in the US. In theory. Also, this is a feature for people who live in America, and mostly irrelevant for everyone in the global south. | | |
| ▲ | gf000 16 hours ago | parent [-] | | As a European, I honestly don't see a difference between the US and China from this perspective. They are both equally untrustworthy in my book. | | |
| ▲ | rrr_oh_man 13 hours ago | parent | next [-] | | As a Western European, I see the same untrustworthiness in Europe. We just have our personal privacy security theater in the form of GDPR and a feeling of moral supremacy that's been drilled into our heads from primary school on. | | |
| ▲ | bigfudge 6 hours ago | parent [-] | | GDPR isn’t theatre in many organisations. Yes large tech firms (mostly US) probably ignore or circumvent. But most businesses I’ve worked for have taken concrete steps to reduce the data they hold and consider how it’s being used asa direct consequence of gdpr. |
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| ▲ | lejalv 13 hours ago | parent | prev [-] | | Don't understand why you are downvoted. |
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| ▲ | dudisubekti a day ago | parent | prev | next [-] | | Artificialanalysis benchmark is a combination of a several benchmarks which might or might not represent realistic coding: "Artificial Analysis Intelligence Index combines performance across 10 evaluations: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, and AA-LCR v1.1." Not saying it doesnt have any value but it's probably irrelevant if you use these AIs for a specific use case. Like for example Humanity Last Exam tests general knowledge, which is not very useful for coding. It's best to go to the specific coding benchmarks and compare there. | | |
| ▲ | aucisson_masque 19 hours ago | parent [-] | | There is too many money involved, benchmark can’t be trusted. | | |
| ▲ | dudisubekti 13 hours ago | parent [-] | | I had a favorite benchmark, SWE-rebench, but sadly it's no longer maintained. But yeah, I'll just take these benchmarks with a grain of salt. Only hands-on experience matters in the end, and these days it's very easy to switch models. |
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| ▲ | KoolKat23 17 hours ago | parent | prev | next [-] | | According my model, My cost is (I use nous as provider) DeepSeek v4-flash-0731
• Your cost: $0.56 DeepSeek v4.1-flash
• Your cost: $1.22 GPT-6 Luna
• Your cost: $4.22 My usage is heavy on the cache. Apparently v4.1 flash uses 1.75 times as many tokens so still cheaper. | |
| ▲ | csomar 21 hours ago | parent | prev [-] | | Does it use less tokens or we just get no accounting of the thinking tokens in OpenAI/Claude models? |
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| ▲ | gizmodo59 a day ago | parent | prev | next [-] | | It’s not direct token to token pricing and everyone misses it. The cost is how much tokens to complete something multiplied by token pricing. I can have a model at .0001 per million tokens but it’s so inefficient that it takes 10B tokens to complete a task means it’s expensive. | | |
| ▲ | sieve a day ago | parent [-] | | I am not designing rockets. Most of my work is bog standard hobbyist stuff: compilers, vms, sandboxes, system tools of various kinds, SSGs, markup languages, plain text ledgers etc. Even Gemma/Qwen running locally can manage this. Frankly, I have no idea what people do with Opus/Fable etc. I don't think anything I do needs something that charges $50/M for output tokens. | | |
| ▲ | apatheticonion a day ago | parent | next [-] | | Can confirm. I have been using DeepSeek since forever and it's so good I was able to write a compiler and native desktop applications with it. I use it as a coding assistant in my IDE so the results end up at the same quality I would write by hand. I recently started a job that only uses Claude models. Opus and Sonnet are so slow you have no choice but to do multiple tasks in parallel. You create a git worktree, set off an agent to do something, another worktree, set out an agent - then play video games for 20 minutes until they complete the task (poorly). You can't really do "guide coding" like you can with DeepSeek-style flash models because Claude is too slow. I think the idea with slow frontier models is to end up with "software factories", where you just write tickets and send them to a harness that delegates work to agents/subagents. Your job is to prompt and review (and eventually just prompt). Mathematically and assuming token prices/efficiency remains constant, the collective US AI industry needs to increase token usage by 15x before 2030 (3.5 years from now) to satisfy investors. With companies already implementing token limits, the only place from here is for frontier models to replace staff entirely to expand budgets for tokens. The only way to do that is to demonstrate the efficacy of software factories and headless agentic workflows. Objectively, I have set up a software factory and I do see the utility of it, though I did it with DeepSeek and prices are 1% that of frontier models - which doesn't bode well for investors looking for an eventual return. Heck, my old M1 MBP 32gb running Qwen 3.6 35b a3b sipping 10w when generating tokens is good enough for a lot of my guide-coding work - it's just a bit slow so I use DeepSeek instead. When hardware prices come down, I honestly wouldn't see a need to subscribe to any service, I'd just grow my own tokens at home. | | |
| ▲ | sieve a day ago | parent | next [-] | | I use Claude Sonnet and ChatGPT via the web UI. I often use Claude to come up with specs for my ideas. This is becoming less and less useful. DS4/MS13/MiMo are almost there for these use cases as well. I dogfood everything I produce, and the models are good at collaborating with me on a spec and then turning it into code. If Sonnet/ChatGPT suddenly became unavailable due to Anthropic/OpenAI suddenly not being able to subsidize the freemium/loss-leader experience, I probably would not miss them. Google/BraveAI already give you the AI experience during search (when you are looking for stuff to buy, or something particular). Claude/ChatGPT still have a minor edge in this use case for me right now. | |
| ▲ | tripzilch 12 hours ago | parent | prev | next [-] | | > running Qwen 3.6 35b a3b sipping 10w when generating tokens is good enough for a lot of my guide-coding work can you tell more about how you're using it? like, what harness? or also in the IDE? I found Qwen3.6 35B/A3B to make slightly too many mistakes (already in its harness' tool use, hence my question), maybe it gets the job done, but it will also sometimes generate a bit of a mess (e.g. editing/creating files in the wrong folders) and fixing/solving its own mistakes takes time (or tokens) .. | | |
| ▲ | Phemist 5 hours ago | parent | next [-] | | I feel like ornith1.5 35B/A3B is an overall stronger model on the same architecture, so a drop-in replacement untill qwen3.8/qwen4 is released. Using the 8bit quant on my M4 max gets around 80tok/sec output/decode on an empty context, dropping down to 35ish on nearly full one. | |
| ▲ | jorgeleo 10 hours ago | parent | prev [-] | | Same thing for me. on an M5 max, Qwen 3.6 35b gives me between 150 and 200 tps using splash as inference engine. More than enough for guided code sessions, at 100% privacy. And i can use obliverated models if i am trying to harden my own app, something i cannot do with cloud providers. | | |
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| ▲ | jklmnopqrstuvw a day ago | parent | prev [-] | | From my own testing, Claude/GPT is much faster than Deepseek. |
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| ▲ | unsupp0rted a day ago | parent | prev [-] | | It sounds like you’re still writing code by hand and reading and reviewing code. For that any decent model from the past year will do. If you want to forget how to write code and not read generated code, then you need a very good frontier model, ideally one from 6-12 months in the future. | | |
| ▲ | darkwater 18 hours ago | parent | next [-] | | This kind of opinion has been around for about 10 months now already, since Opus 4.5 and Claude Code initial release. It just shifts alongside models. | |
| ▲ | sieve 20 hours ago | parent | prev | next [-] | | I used to read the code till around May. Now I don't. Instead I validate behavior. And have multiple LLMs verify that the code implements my handwritten spec. MiMo 2.5/2.6, MuseSpark 1.3, DeepSeek V4/4.1 Flash and GLM 5.3 Flash are perfectly capable of following my spec and then poking holes in the implementation till there are none left. | | | |
| ▲ | locknitpicker 20 hours ago | parent | prev [-] | | > It sounds like you’re still writing code by hand and reading and reviewing code. This is such a naive, baseless opinion. Nowadays any AI coding assistant service supports or can be used with sub-agent orchestration frameworks. If you are in the business of software factories, you can use the cheapest models and even local models to handle some if not all tasks in the orchestration chain. Adding tests or executing tests (unit, integration, UI, you name it) doesn't require a cutting edge frontier model. Neither does refactoring. Neither does identifying call stacks. Neither does planning a changeset. You have your specialized subagents, you put together a small orchestrator subagent that handles feedback loops and handoffs,and you throw it at tasks. For the past couple of months, most of the code I write is not code per se, it's subtask orchestrators. And unlike the old "only Opus is passable" days, the cheapest models do get the job done. |
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| ▲ | MitziMoto a day ago | parent | prev | next [-] | | These are also the orders of magnitude of our production agents for our business (NOT coding). Cache reads are so heavy compared to anything else that it's the only price point that really matters, regular input and output are negligible. I need aggressive cache read pricing with full prompt_cache_key support to have a model be financially viable for our workload. Right now Meta Muse 1.3 Contributor is the only one that makes sense--but we are starting Evals on the new MiMo 2.6 class to see how it holds up. | | |
| ▲ | sieve a day ago | parent | next [-] | | I have used MiMo 2.5 extensively. MuseSpark and DS4 Flash are MUCH smarter than that one. But MiMo follows instructions diligently. So it has been useful as the implementer of a spec designed by Claude/Kimi. One good thing about MiMo that I experience on OpenCode is the provider seems to cache tokens for much longer than MS13/DS4F. I have seen cache being hit for close to an hour after the last request. The corresponding timing for MS13/DS4F is in the 1-5 min range. I am trying out MiMo 2.6 Flash as well. | |
| ▲ | gleenn a day ago | parent | prev [-] | | Last I heard, caches had like a 5 minute TTL... doesn't that mean if you get up and make a coffee (hand pour over of course), that you are back at full price? | | |
| ▲ | jmalicki a day ago | parent | next [-] | | I wish that was more programmable. You can pay for higher cache time, you can pay for NVMe KV cache for an hour that can just be reloaded, etc., at a lesser tier you can pay for the KV cache to be stored on a network store (I guess I'm unclear if that last tier would be cheaper than recomputation, not even 100% sure of the NVMe with direct GPU<->storage DMA) depending on your model settings. | |
| ▲ | MitziMoto 21 hours ago | parent | prev [-] | | [dead] |
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| ▲ | WinstonSmith84 19 hours ago | parent | prev | next [-] | | Maybe your numbers are right, but that's not been my experience. My typical workflow is Astra coordinating with Luna Max (5.6 back then) as both implementer and reviewer and sometimes Astra review as well when I've some distrust with Luna .. A day, I've been trying to replace Luna Max by Deepseek v4.1 flash and I've been burning about $7 worth of tokens in Fireworks in a single day. More than what my 20x OpenAI sub costs me, including Astra usage. And that was when Luna 5.6 was less capable and more expensive than Luna 6.0. | | |
| ▲ | sieve 17 hours ago | parent [-] | | I have written about my experience. I have also mentioned the kind of code I write. It is not react/js/css heavy stuff that I see a lot of people write. So the code bases are typically in the 5-50KLOC range. Freestanding C, Python, or maybe some TypeScript. And fairly modular. I can thus run models on specific modules without having them read everything into context. So the workflows I mention work for this kind of stuff. |
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| ▲ | ascorbic 16 hours ago | parent | prev | next [-] | | You can't compare a subscription to API prices. OpenCode Go is massively subsidised. Unlike the closed labs, we can say that for sure because we can see what they're paying for their tokens. | |
| ▲ | handfuloflight a day ago | parent | prev | next [-] | | How long can OpenCode bleed for? | | |
| ▲ | sieve a day ago | parent | next [-] | | Are they bleeding? Their multipliers seem to be reasonable. They are not offering $60 worth of usage for $10 on every model, only some. In the case of the expensive ones, it is only $15. Given how subscription models work (not every one uses every last $ of their plan), they should achieve breakeven soon enough I guess. | |
| ▲ | ronsor a day ago | parent | prev [-] | | They already stopped. That's why the service quality declined. | | |
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| ▲ | infecto a day ago | parent | prev | next [-] | | How can you compare a subscription which is most likely being subsidized with consumption pricing? | | |
| ▲ | sieve a day ago | parent [-] | | I gave you the $40 option. Which is what it would cost if you used APIs on OpenRouter or elsewhere. Still beats Luna by 4-4.5x | | |
| ▲ | infecto 11 hours ago | parent [-] | | Ok great. I still don’t see how subscription costs can be compared to API. |
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| ▲ | dcl a day ago | parent | prev | next [-] | | How have you found Muse Spark 1.3? It doesn't get much mention, despite pretty good benchmarks. I've been using a bit at home and find it quite good, often finding mistakes made by Opus 5. | | |
| ▲ | sieve a day ago | parent | next [-] | | MS13 is pretty sharp and has been my workhorse for the past month. It follows my coding style and commit/clean workflows referenced in AGENTS.md perfectly but has the habit of doing things without conferring with me (the Gemini problem). So you need some kind of instruction for that. It starts failing around the 5-600K context mark, but you can have it generate a handover document and continue in the next session. I would not use it at sticker price, but the Contributor version is priced just about right. | | | |
| ▲ | slopinthebag 19 hours ago | parent | prev [-] | | shocking. the code it generated, while technically working, was entirely garbage. i used it for code review and it flagged twenty issues, sol checked the review and found 75% of them were hallucinations. sol was much closer to reality. i no longer trust benchmarks at all because of it. |
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| ▲ | a day ago | parent | prev | next [-] | | [deleted] | |
| ▲ | attentive 20 hours ago | parent | prev [-] | | apples and API pricings | | |
| ▲ | sieve 18 hours ago | parent [-] | | You can use the models I mentioned directly from DeepSeek, Meta and Xiaomi and not exceed $40. Were it not for GLM 5.3 blowing up a quarter of my monthly budget in 5h, we are actually looking at something like $30. |
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| ▲ | booty a day ago | parent | prev | next [-] | | I dont know how they make money here
Well, here's the neat thing: they don't!Snark aside, Luna 5.6 was (is) an incredible game-changer. | | |
| ▲ | larodi a day ago | parent | next [-] | | > Well, here's the neat thing: they don't! perhaps it then does mean - squeeze as much as you can get off this actual free usage. | |
| ▲ | adventured a day ago | parent | prev | next [-] | | Luna is about suppressing inexpensive Chinese model competition. It's super simple. Gigantic hyper margin ad network = artificial subsidization of cost for various tiers = put the boot on the neck of Chinese competitors. There's no scenario where they can compete with what advertising margins make possible in terms of artificially lowering prices charged. | | |
| ▲ | mordae 18 hours ago | parent | next [-] | | Chinese buy their tokens at home. West as a market is an afterthought for their companies them. Western AI is banned, so only used via resellers by small fish, not companies. US has zero presence at that huge market, and absolutely not a moat. They are buying Huawei accelerators in bulk to serve their local customers. The whole system is currently optimized to deliver a lot of cheap LLMs and hardware for them to run on. | |
| ▲ | locknitpicker 19 hours ago | parent | prev [-] | | > Luna is about suppressing inexpensive Chinese model competition. I think so too. To me the so-called Chinese local models are a clear move to prevent US companies to establish a foothold and build a moat around their business. US companies are clearly invested in a strategy to make themselves relevant with claims of major impressive achievements with the so called frontier models, and how these and only these are unblocking whole ranges of applications. At the same time, they are heavily invested in pushing AI on all absurd types of mundane tasks, such as transcribing meetings and... talking to your own kids? In the meantime it's rather obvious that, in spite of all the propaganda, frontier models are required only in ultra niche applications, whereas the ability to run any model at all already provides most of the value. In fact, US companies have been renownee by dumbing down older generation models in what seems to be a desperate attempt to make newer models look better and influence their uptake rate. So there is no better way to take the wind out of the US AI companies' sail than pulling a two-punch attack consisting of not inly releasing capable models that refute the "only US frontier will do the job" thesis but also releasing them for free to commodities them and eliminate the business impact of dumbing down models. | | |
| ▲ | idbnstra 11 hours ago | parent [-] | | > and... talking to your own kids? i don't doubt they're pushing for using AI for that, but i'm curious of examples of where they're doing this. commercials, ads, etc. | | |
| ▲ | locknitpicker 9 hours ago | parent [-] | | > i don't doubt they're pushing for using AI for that, but i'm curious of examples of where they're doing this. commercials, ads, etc. You just be living under a rock. Not do long ago Sam Altman was floating this fantastic usecases for AI was to have it explain to you your kids interests, and have it create a podcast for you to be able to keep in touch. |
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| ▲ | atoav a day ago | parent | prev [-] | | "We lose money on ever sale, but we plan to make it up in volume" | | |
| ▲ | Barbing a day ago | parent [-] | | *govt bailouts | | |
| ▲ | adventured a day ago | parent [-] | | They're closing in a billion users. That's Google search territory. OpenAI is sitting on a $100+ billion ad network, incoming. They're not going to need a government bailout, they're going to be a spigot of cash production. Every single thread on HN keeps saying the same ridiculous thing, going on a year now. It's like they've never heard of advertising, which SV specializes in. It's like they're oblivious to the fact that every mega platform with so many users becomes an ad goldmine, and GPT's context positioning is even richer than search. | | |
| ▲ | locknitpicker 19 hours ago | parent [-] | | > OpenAI is sitting on a $100+ billion ad network, incoming. How can you make this sort of claim with a straight face, knowing that a chinese model downloaded for free from ollama works as well if not better than OpenAI's models, without costing you a cent. | | |
| ▲ | Barbing 19 hours ago | parent [-] | | I guess it’s assuming the fact ChatGPT is a household name will bring it near permanent relevancy? I’m skeptical. And sorry to the parent commenter if I’m making a bad assumption. |
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| ▲ | krat0sprakhar a day ago | parent | prev | next [-] | | 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) :) | | |
| ▲ | jadbox a day ago | parent [-] | | 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). | | |
| ▲ | antupis a day ago | parent | next [-] | | Flash thinks much more so it’s pretty much line with Sol for performance. That said I like flash coding style much more than OpenAi models. | | |
| ▲ | jeffnash a day ago | parent [-] | | out of curiosity, what type of code/language do you usually use flash to write? | | |
| ▲ | spockz a day ago | parent [-] | | I use it for golang, and it is fantastic. Incredibly fast. It seems the llm and I “understand” each other. I have to be less careful in my exact phrasing. It kind of just does what I want and expect. When I ask for an explanation it adds the right amount of detail. Of course, some of the material is new to me so subtle errors are hard to spot. But at least I’ve caught Terra and Sol on inconsistent messaging. Also I’ve found 3.8 flash to circle back to root issues even at the conceptual level like problem fit and conceptual solution direction or architecture when I wasn’t achieving my goals. It flat out said I was attempting to use the wrong tool. Whereas Sol and Astra kept rabbit holing and looking for tiny implementation errors. Even after prompting them specifically to look at it broader. | | |
| ▲ | timattrn a day ago | parent [-] | | what harness or plan are you using 3.8 flash with? | | |
| ▲ | spockz 20 hours ago | parent | next [-] | | I’m using antigravity. I’m still on the AI Pro plan for the promotional $5/month. | | |
| ▲ | desterothx 18 hours ago | parent [-] | | where is this promotion? | | |
| ▲ | spockz 18 hours ago | parent [-] | | If you don’t have a plan yet, log in to antigravity. There will be a button “upgrade plan” somewhere. Sometimes it pops up and otherwise lookup in settings > account. There should be some button that says upgrade. Clicking that brought me to the google studio ai page which offered the 20-something plan for €5/month. |
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| ▲ | Kostchei 20 hours ago | parent | prev [-] | | anti-gravity with gemini 3.8 or gtfo |
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| ▲ | krat0sprakhar a day ago | parent | prev | next [-] | | TBH: I really like how fast 3.8 Flash is... Once I have clear plan, I feel quite confident in delegating large parts of implementation to Flash and Luna | | |
| ▲ | mgkimsal a day ago | parent [-] | | Maddening for a bit - I've got problems that Flash is better on, and some Luna is better on, but I generally don't know until one has wasted time/tokens. Then I switch to the other one and... it's often just... bam - done. Correctly. I can't find the patterns ahead of time to determine what model I should be using first. :/ That said, I've been alternating between both the last month or so and they've both been pretty good compared to earlier models. | | |
| ▲ | Kostchei 20 hours ago | parent [-] | | codex seems pretty solid on review, flash is fast on basics but makes more mistakes/errors, Claude is just to picky for me |
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| ▲ | oh_no a day ago | parent | prev | next [-] | | look at token use, 3.8 flash is a huge token hog compared to openai models | |
| ▲ | Citizen_Lame a day ago | parent | prev [-] | | Gemini 3.8 Flash and 3.1 Pro are pure rubbish. Very little thinking, mediocre and usually incorrect results. They cannot be compared to frontier models. | | |
| ▲ | anukin a day ago | parent [-] | | This is my experience as well. I am surprised that lot of people find it much better than Luna. | | |
| ▲ | mapontosevenths a day ago | parent [-] | | I suspect that the people saying this haven't used Luna. It's also weird that anyone uses it outside of an enterprise. They force you to use Googles inferior harness on the plans and I doubt any mere mortal is paying that much, for so little usage, with the worst harness on the market. | | |
| ▲ | bonestamp2 18 hours ago | parent [-] | | I prefer 5.6 Luna while a coworker prefers 3.8 Flash. The difference seems to be that they chat with Flash (with code context) while I just ask Luna to directly modify the code. I was already very impressed with 5.6 Luna so I am looking forward to running 6.0 Luna all day tomorrow to see how it compares. |
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| ▲ | user43928 a day ago | parent | prev | next [-] | | 6-luna is no improvement over 5.6, merely a price cut. And info from the help page with message limits suggests the 50% price cut does not apply to the subscription, where they applied only a 1/3 price cut instead. I'm not thrilled with this release. Opus 5.5, which matches GPT-6 Astra performance at a cheaper price, is much more interesting. | |
| ▲ | InsideOutSanta a day ago | parent | prev | next [-] | | > I dont know how they make money here By raising it from investors. | | |
| ▲ | GolfPopper a day ago | parent [-] | | To whom they promise the Sun, the Moon, and the Stars. Roflmao. Whatever the merits of the underlying technology, the business model is pure hucksterism. |
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| ▲ | the__alchemist a day ago | parent | prev | next [-] | | How does 6-Luna xhigh compare to 6-Sol medium? Or more broadly newer/bigger model with lower effort vs older/smaller higher effort? | | | |
| ▲ | zozbot234 a day ago | parent | prev | next [-] | | MiMo 2.6 Pro is at the Pareto frontier (the one where you only need 20% of the smarts for 80% of the tasks) according to Artificial Analysis, nicely filling in as a substitute for a hypothetical 'GPT-6 Terra' (which doesn't exist as far as we know). That's pretty darn impressive from an open model. | | | |
| ▲ | oblio 16 hours ago | parent | prev | next [-] | | > I dont know how they make money here That one's easy, they don't make money. | |
| ▲ | m101 a day ago | parent | prev | next [-] | | perhaps they use this as the carrot to get you locked into their monthly plan over anthropic's. | | | |
| ▲ | 7777777phil a day ago | parent | prev | next [-] | | I guess I have to update my pareto front then: https://philippdubach.com/posts/jev-model-router-for-pi/ | |
| ▲ | iwontberude a day ago | parent | prev | next [-] | | [dead] | |
| ▲ | arcanemachiner a day ago | parent | prev | next [-] | | > I dont know how they make money here I assume it's a subsidy to get more training data. EDIT: Okay downvoters, what's your take on why they're giving away Luna for so cheap? | | |
| ▲ | tedsanders a day ago | parent [-] | | By default, OpenAI does not train on API data. I promise you that Luna's low pricing is not a subsidy to get more training data. We've been lowering prices for years. (I work at OpenAI.) | | |
| ▲ | arcanemachiner 21 hours ago | parent [-] | | Wait, so you guys don't anonymize the user data, then train on it after it's been sanitized? I thought this was done to some degree or another. So what is the value prop then? Just basic supply and demand? FWIW I have definitely noticed OpenAI's emphasis on efficiency and value in the last year, so that part isn't new to me... I just thought there was more to it then that. | | |
| ▲ | tedsanders 18 hours ago | parent [-] | | API: By default, no training (opt in). ChatGPT enterprise: By default, no training (opt in). ChatGPT personal: By default, training (opt out). |
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| ▲ | lacker a day ago | parent | prev [-] | | Offering Luna for cheap is like restaurants giving you free bread and water. They're pretty sure that you're going to end up eating the expensive stuff on the menu. | | |
| ▲ | usef- a day ago | parent [-] | | Note that to sit at a restaurant you're obliged to order something, though. Here there is no obligation to go beyond the model you choose. |
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| ▲ | matznerd a day ago | parent | prev | next [-] |
| Simon, love your work, one piece of minor feedback for the individual model pages is to make the font of the model name potentially bigger than (and above) the conversation id (which means nothing to the audience) "2026-09-22T18:28:00 conversation: 01m355zvyw8946qyraa8zpz6h9 id: 01m355zvyx47zxx5c6q6b3fg0m#". I had all the tabs open individually and harder to scan which model is which... otherwise keep up the great work! I like the grid view a lot. (Also the pages have no OG images set, which impacts what the link looks like shared)... |
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| ▲ | simonw a day ago | parent [-] | | That's a good idea. It's the default output for my `llm logs` command, but that header could at least show the model ID. OG images will require me to move away from publishing in a Gist and linking to from a JavaScript page that loads the Gist. Probably worthwhile though. | | |
| ▲ | matznerd a day ago | parent [-] | | I think you can make it work without leaving Gists by using a Cloudflare Worker as a workaround. The Worker sits in front of the renderer page and adds the og tags to the HTML before it's sent out. You'd also need to turn the SVGs in the Gist into a PNG for the og:image, and decide if you want a grid or just one image, any text formatting, and how long to cache... I got it working in a quick local test (grid of all the reasoning efforts, cached per Gist, loads from the raw Gist URL so it doesn't hit the GitHub API rate limit). Code + prompt + notes here:
https://gist.github.com/matznerd/ece297107bd99ac028c7962c217... Basic concept is to: 1. Put a Worker on the /markdown-svg-renderer route. Normal visitors get your page exactly as it is now. 2. When a link has ?url=<gist>, the Worker reads the Gist and adds og:title, og:description and og:image to the page's HTML. Link previewers like Slack and iMessage don't run JS, so this is the only way they see them. 3. og:image points to a second Worker URL (og.png?url=<gist>). It takes the SVGs from the Gist, puts them in a grid, and converts it to a PNG, since previewers won't show SVGs. 4. Both results get cached per Gist, so each Gist is only fetched and rendered once, even with a lot of traffic. Things to customize: - Title and description (mine: "gpt-6-luna SVG of a pelican riding a bicycle" / "6 runs, reasoning effort none to max") - Grid of all runs vs just one image, plus layout, labels and font - How long to cache (I used a day, but edited Gists keep the old preview until it expires) |
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| ▲ | Cu3PO42 a day ago | parent | prev | next [-] |
| 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. |
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| ▲ | gtirloni 20 hours ago | parent | prev | next [-] |
| What's the relevance of the pelican benchmark when models probably saw it during training? Didn't OpenAI stop testing against SWE-Something because it was tainted? |
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| ▲ | simonw 14 hours ago | parent | next [-] | | If they train for the benchmark, how come many of the pelicans produced by their different models at different reasoning levels still suck? That aside, the relevance these days is in comparing models and effort levels within the same model families - hence the comparison grids. | |
| ▲ | genidoi 20 hours ago | parent | prev [-] | | It's not a benchmark, it is a meme benchmark. | | |
| ▲ | a3w 18 hours ago | parent [-] | | Memes are arguably the web scale of benchmarks. | | |
| ▲ | ljm 14 hours ago | parent [-] | | AI reproducing Xtranormal video clips like NodeJS Is Web Scale should be the new benchmark. If the dialogue is slop and not like the old memes then it fails. |
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| ▲ | saretup a day ago | parent | prev | next [-] |
| Not that this benchmark is super relevant anymore but these look worse than I expected. |
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| ▲ | simonw a day ago | parent | next [-] | | 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. | | |
| ▲ | hdz a day ago | parent | next [-] | | Tons of value left, especially for open source models. I would say the benchmark is yet to be truly saturated (just look at the legs and seat to see what I am talking about) and I always look forward to seeing them. Thank you! | |
| ▲ | Kotlopou a day ago | parent | prev | next [-] | | To me the main upshot of this benchmark is precisely that the pelicans still usually look a bit wonky. It's bizarre, since this definitely has a good solution, but it's in line with my experience that memorization of the training set just... isn't happening very much? As in, whether a model fails or not doesn't have much to do with whether that exact question was likely posed many times before. | |
| ▲ | nomel a day ago | parent | prev [-] | | I think some additional value would be had by seeing how well it can modify the pelican. Like, "now facing left", "sitting on the handlebars", or "with green spokes" to see if it can break out of some pretty obvious statistics in the training data! And, there's always asking for an STL rather than an SVG! |
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| ▲ | alansaber a day ago | parent | prev [-] | | It would be extremely funny if the explosion in SVG generation capability in particular was a result of this benchmark |
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| ▲ | mkotlikov a day ago | parent | prev | next [-] |
| How come the pelicans get older with more reasoning? Is GPT 6 taunting us with our mortality? |
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| ▲ | zahlman a day ago | parent [-] | | Probably it's easier to convey youth than age with a lower level of detail. |
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| ▲ | dom96 a day ago | parent | prev | next [-] |
| It's surprising but MiMo V2.6 Pro performs better and is cheaper than GPT 6 Sol on my benchmark[1]. Open weight models are really snapping at the heels of the major western models. 1 - https://bench.killswitch-lang.org |
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| ▲ | dmazin a day ago | parent | prev | next [-] |
| > 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. |
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| ▲ | agentcoops a day ago | parent | next [-] | | I’ve been doing really heavy text analysis work with LLMs where false negatives/misses are important to minimize and my god did I hit cost thresholds quickly with 5.6 Luna — it was the first time I felt motivated to seriously work with local open models, even if inference was degraded for the task. Cheaper and much better inference now brings me back to the closed models for better or worse. | |
| ▲ | FusionX a day ago | parent | prev | next [-] | | 5.6 Luna was already discounted at half the price on OpenRouter. Looks like they made it permanent. | |
| ▲ | onlyrealcuzzo a day ago | parent | prev | next [-] | | Hopefully Terra 6 slots somewhat nicely into this space. | |
| ▲ | user43928 a day ago | parent | prev [-] | | Yes, I am mildly disappointed with these releases. I expected a Fable 5 -> Opus 5 situation, where GPT 6 Sol would perform on par with GPT 6 Astra. Instead it's more like a price cut on GPT 5.6 Sol, and I'll have to stick with Astra for my work. The only thing I can hope for is that more users switching to the GPT 6 Sol model frees capacity, allowing OpenAI to hand out some usage resets. | | |
| ▲ | zigzag312 17 hours ago | parent [-] | | Yeah me too. Maybe that place will occupy the Astra Minor model that appeared in Microsoft's Azure model config. As Sol and Sonnet are now similarly priced (unless Sonnet 5.5 will reduce its price). | | |
| ▲ | user43928 16 hours ago | parent [-] | | Good point! Maybe they are keeping the cheaper Astra alternative back for their Dev Day next week Tuesday. |
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| ▲ | psma_egeliaa a day ago | parent | prev | next [-] |
| What's with the radial spokes? When are we gonna start seeing proper cross lacing? |
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| ▲ | adverbly a day ago | parent | prev | next [-] |
| Many of them still get the layers wrong. They put both legs on the same side of the bike. Even Astra max which actually put one leg on each side of the bike still somehow messed it up because when it added the bike chain, it put the left leg between the bike chain and the frame. |
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| ▲ | teiferer 12 hours ago | parent | prev | next [-] |
| > The grid is actually really interesting, because it shows that the 5.6 family default to brighter colors than the 6 family. Could you elaborate on what it is about that observation that is "really interesting"? It is a fun detail, but does it actually mean anything for usefulness or progress or anything really beyond "gpt-6 makes darker colors"? Not trying to dismiss your work, to the contrary. I'm wondering if I'm mising a deeper insight here. |
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| ▲ | simonw 11 hours ago | parent [-] | | It shows that the three 5.6 models are closely enough related that they exhibit similar "taste" in their color choices, and the same is true for the 6 models. |
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| ▲ | FranklinMaillot 16 hours ago | parent | prev | next [-] |
| What surprises me every time with the pelican benchmark, is that drawing style is very consistent within each model across, what I believe, are independent sessions. Same tones, similar background... Just more refined with increasing effort. I would expect much more variability. |
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| ▲ | shepherdjerred a day ago | parent | prev | next [-] |
| Wow I cannot believe Luna is getting even cheaper. IMO this is the model that is going to change the world. Everyone said tokens were too expensive but these are getting close to free while still having fantastic performance. |
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| ▲ | pantsforbirds a day ago | parent | prev | next [-] |
| The sol max looks like it's absolutely ripped for some reason |
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| ▲ | sfblah a day ago | parent | prev | next [-] |
| Yep. We just switched several classification jobs we run over to gpt-6 luna. Love the cost savings. |
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| ▲ | batperson a day ago | parent | prev | next [-] |
| I've been sharing that pelican grid in my circles a whole bunch, it's great! I think only one data point is missing, generation speed. Would be interesting to see how the reasoning level/token counts relate to speed. |
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| ▲ | ksec 18 hours ago | parent | prev | next [-] |
| I am starting to wonder if this test is now being heavily benchmarked internally we should be using some new test? |
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| ▲ | rayiner a day ago | parent | prev | next [-] |
| It's funny that even Astra doesn't know you ride a bike by straddling it between your legs. (EDIT: Oh, I guess Max gets the occlusion. But it doesn't realize it has to pick direction the knee bends in.) |
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| ▲ | nicolamanzini a day ago | parent | prev | next [-] |
| Here are some somehow standardized pelican tests but for 3d scenes in threejs at threejseval.com Luna 6 High: https://threejseval.com/models/gpt-6-luna-high Sol 6 High: https://threejseval.com/models/gpt-6-sol-high You can compare any other model on the same prompt. Gallery unlocks after 4 votes: https://threejseval.com |
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| ▲ | NichoPaolucci a day ago | parent | prev | next [-] |
| Simon - I believe you've been doing this with a "one-shot" approach. Have you ever considered seeing what the results are with a few more prompts? Maybe 1,2,3 adjustments? Something like the astra MAX is pretty darn good - but something is up with the right wing and the right foot (flipper?) I bet each of these could be modified to be significantly better with 1 or 2 "rounds" of adjustments. (Others not so much). Obviously, not as deterministic as your single prompt approach, but something I just thought of while thinking about the price (Because wow! For some of these I'd expect a usable SVG after that much). |
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| ▲ | simonw a day ago | parent [-] | | Yeah, I have a couple of variants that I want to get working: 1. Each model gets three chances, and then gets to pick the best according to its vision input 2. Models run in a loop where they can produce SVG, see it rendered, and then edit it further I tried that loop last year and had disappointing results, but the models are a lot more effective this year. |
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| ▲ | idk1 a day ago | parent | prev | next [-] |
| What I overwhelmingly love about that Pelican grid is the two best ones, they've put a neck scarf on to show speed and wind. |
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| ▲ | norman784 a day ago | parent | prev | next [-] |
| 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 |
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| ▲ | simonw a day ago | parent | next [-] | | The table on https://developers.openai.com/api/docs/pricing is more readable: +--------------+-------+--------------+--------------+--------+
| Model | Input | Cached input | Cache writes | Output |
+--------------+-------+--------------+--------------+--------+
| gpt-6-luna | $0.10 | $0.01 | $0.125 | $0.50 |
| gpt-5.6-luna | $0.20 | $0.02 | $0.25 | $1.20 |
+--------------+-------+--------------+--------------+--------+
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| ▲ | norman784 a day ago | parent [-] | | Yeah, how they put, is confusing to me, they should have put that table instead of what they have right now in the article. |
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| ▲ | tedsanders a day ago | parent | prev [-] | | Yes, GPT-6 Luna is 50%-58% cheaper than GPT-5.6 Luna. (I think the blog text and graphs make it pretty clear.) | | |
| ▲ | norman784 a day ago | parent [-] | | Yeah, but it confuses me, I read left to right, so if they put GPT-6 and $0.20 first, I would assume that's the new pricing, they should make it clear, not confusing. |
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| ▲ | dbbk a day ago | parent | prev | next [-] |
| If you're happy with letting Meta train on you, Muse Spark 1.3 Contributor pricing is a much better deal than Luna |
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| ▲ | myrmidon 14 hours ago | parent | prev | next [-] |
| Damn, Astra-Max looks really good at first glance, it even has the legs on the correct side of the bike (z-order for chain is still wrong though). I find it really interesting how consistent the layout is for these (facing right, with the sun in the top right). Just a little more progress on physically correct z-ordering and these won't be easily identifiable as slop anymore :O Your observation with the grid comparison is quite interesting. I wonder if that could be generalized into capturing some kind of aggregate mood/attitude for different LLMs when picking (multiple?) suitable things to compare... |
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| ▲ | alexforster 21 hours ago | parent | prev | next [-] |
| Your benchmark started being gamed by the frontier models a year ago though. The original idea (find a quirky way to test models with something they don't optimize for) is great, but it needs a refresh. |
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| ▲ | arcanemachiner a day ago | parent | prev | next [-] |
| > half the price of GPT-5.6 Luna Half the price when it launched, or after the price dropped by 75%? |
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| ▲ | user43928 a day ago | parent [-] | | After the price drop. GPT-6 Luna does not perform better than 5.6, so they can't raise the price. |
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| ▲ | viraptor a day ago | parent | prev | next [-] |
| > Error: Gist API returned 403 Is what I'm getting on the top two links. |
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| ▲ | addaon a day ago | parent | prev | next [-] |
| Is Luna (on "low" thinking) the first left handed model? |
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| ▲ | ChickeNES a day ago | parent | prev | next [-] |
| > GPT-6 Luna being half the price of GPT-5.6 Luna is a really big deal. good god |
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| ▲ | aidos a day ago | parent | prev | next [-] |
| That GPT-6 Sol max pelican looks… so old and depressed. |
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| ▲ | order-matters a day ago | parent | prev | next [-] |
| out of curiosity, do you retry the same model multiple times to see the range of output it comes up with? or is it purely a 1-shot test |
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| ▲ | saltysugar a day ago | parent | prev | next [-] |
| Isn't everyone pelican-maxxing these days? |
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| ▲ | redsaber a day ago | parent | prev | next [-] |
| looks like they're positioning luna to tackle the low-cost cn models |
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| ▲ | hamrocksissors a day ago | parent | prev | next [-] |
| Out of all of the benchmarks out there, pelican bicycle bench is the only one I care about. Thank you Simon. |
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| ▲ | jdw64 a day ago | parent | prev | next [-] |
| 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... |
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| ▲ | loeg a day ago | parent [-] | | And the bicycles have weird dimensions -- extremely slack head tube angle, handlebars in the wrong orientation, etc. | | |
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| ▲ | nanook a day ago | parent | prev | next [-] |
| 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. |
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| ▲ | aussieguy1234 a day ago | parent | prev | next [-] |
| Pelicanbench |
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| ▲ | lofaszvanitt a day ago | parent | prev | next [-] |
| Pelicans gonna devour capibaras if they see these depictions. |
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| ▲ | ijidak a day ago | parent | prev | next [-] |
| What I like about the grid of SVGs is from I can see that Astra high seems to yield similar quality and price to Sol 6 max. And Astra medium seems to yield similar or better quality for the same price as Sol 6 xhigh. |
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| ▲ | varispeed a day ago | parent | prev | next [-] |
| 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. |
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| ▲ | inshard a day ago | parent | prev [-] |
| My new sub-benchmark is which combinations achieve the hook at the end of the upper beak. Right now just 4: Astra Max, XHigh and Medium; GPT 6 Sol Max |
