You learn something every day. Today, it was the term "systolic array": A systolic array is a specialized grid of simple, interconnected processing units designed to execute parallel data operations—like matrix multiplication—by rhythmically passing data directly from cell to neighboring cell without writing intermediate results back to main memory.
The term comes from the biological word systole (the contraction of the heart pumping blood through the body). In a systolic array, data "pulses" through a network of processing elements on every clock cycle, driven by a global clock beat.
The subsidized subscription model won't last, API pricing "feels" closer to a true sustainable business model.
They are using their tried and tested formula of first getting you addicted to cheap shit....
they know it always works because ppl cannot see( or question) beyond all the cheap shit they are getting.
yea i got that from your first comment ( although you removed crush American companies in _price_ ). you are pro cheapness at any cost even if its from your country's state funded direct geopolitical enemy.
China can always count on first order greed to win
I've used it in some open source code though, and loved how fast it was.
My mind is changing on how valuable my code actually is though... it's the complete picture, how it's put together, the design, the UI, the attention to detail that's the real value.
It’s so cost effective I can offer a generous free tier since my goal isn’t to make money with it.
What's difficult and doesn't have to be with philosophy/ spirituality is to find relevant bits off situation, theme etc.
This app does that very well, LLMs are good at entity recognition.
One feature of the app is that all scripture is verified and what’s show to the user doesn’t come from the LLM at all and instead a trusted source.
I think exploring scripture this way does not alleviate you from struggling to learn and apply it. It hasn’t for me.
But there are ways to control and constrain the LLMs and what the user is presented with.
These are all top of mind for me and why I felt there could be a better option than asking ChatGPT directly.
I'm on a team that develops a Bible study app, and we're all relatively content with how the basic models converse regarding scripture. Even as far back as GPT-4 was excellent. They occasionally have minor hallucinations (a dealbreaker for a production app), but they do an excellent job with theology and Bible scholarship, given reasonable guardrails.
I'll admit I'm coming from the perspective of "should we be implementing this?" It seems, on the surface, that a strong embedding-based verse retrieval covers the bases at a microfraction of the cost.
If you're interested, check out the development server where we're working on this. You navigate to the search (magnifying glass) and then hit "Meaning". Sorry for the confusing route; we're still deciding on back-end details and haven't focused on the front yet.
So it’s less about model choice and more about governance of scripture.
I will check out the link you sent for sure!
Anyways, impressive app! We haven't tackled such an ambitious project just for it being daunting.
flash is suitable only for a toy apps, not for production environments :)
Deepseek v4 Pro prices with Opus 5 perf would be freaking unbelievable!!
This is probably a dream.
https://artificialanalysis.ai/models/deepseek-v4-flash?intel...
First, your direct comparison, Deepseek V4 Flash 0731 (max effort) $0.03 (rounded up) per task @ index 50.
OpenAI Luna:
* high effort $0.03 (rounded down) @ index 46
* xhigh effort $0.04 @ index 49
* max effort $0.07 @ index 51
So I would say a fair statement would be "OpenAI Luna between 2x and 3x the price of Deepseek Flash, what you get is 2 to 5 times faster inference"
The cheapest OpenAI model that beats it is OpenAI Luna (max effort) $0.07 @ index 51 (if you take the rounding out it summarizes to triple the price for similar performance), but still close to 3x faster.
And can SOMEONE please tell artificialanalysis that using dark blue for both Deepseek AND OpenAI is an especially unfortunate choice of colors, especially today?
uhh openai is dark gray: `rgb(31, 31, 31)` and i'm pretty sure it always has been?
For simple tasks, they're already saturated, and you'd prefer the faster model, so that you can have a realtime/interactive-ish experience.
Or to put it bluntly, it's cheaper if you don't value your time. That goes for smaller models in general -- need more handholding, more correcting -- but the Chinese ones are slower on top of that.
As for speed, Sol on Low is faster than Luna on most settings.
It’s also so inefficient, when they release the full performance numbers it’s not going to be good.
One example, it takes about 3.6x more tokens to finish the same work as Gemini Flash 3.6.
Mind you, until the recent price cuts to Luna - Gemini 3.6 Flash wasn't even egregiously priced (but oh how things change in just 1 week).
Does the file hosting actually cost peanuts when you do it yourself and the cloud has shattered my understanding of what it actually costs to deliver so much data?
If the full non-flash model follows up with the expected improvements, and at the price point they've been keeping, it puts the frontier labs in a tough position and it feels to me like like OpenAI is reaching deep into their pockets to try to head that off.
TFA link is a 404 though. I'm reading through https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731 instead
Am I just using it on tasks that makes it go on forever vs these benchmarks that are short&sweet, or something like that? I've been throwing bunch of identical prompts at different models at the same time, and when comparing hy3 and K3 I've never once had K3 reason less than hy3, as just one anecdotal data point.
Similar price? Doesn't make sense. Maybe they meant power, capability or speed?
Why do the cache hit rates seem to vary so much between harnesses?
I use pi, which is very minimalist, and I get a hit rate of ~99%. Paying like $1 a day for Flash. Yet, the hit rate mentioned on OpenRouter is only ~79%.
BTW, this is one of the things that I really like about Pi. It’s very simple and thus very predictable.
[0] https://petergpt.github.io/bullshit-benchmark/viewer/index.v...
The specific agent is focused on getting precise and on point answers about a codebase.
The starting point was nowhere near. E.g. asked why was X implemented in a certain way it would give bogus answers when the real answer was that there was no reason at all.
The benchmark included more than 50 questions or different difficulty.
But when the agent was improved in its prompt and rooting it was impossible to have it perform worse than closed source sota.
Just to say that the quality of the harness is as important as agents intelligence.
Or a benchmark to benchmark benchmarks?
benchmark website benchmark is indeed a benchmark that benchmarks websites with benchmarks (but it can be shown outside websites as well, it's not picky)
Daily reminder that improving your samplers from the garbage default top_p/top_k to min_p or subsequent methods dramatically improves the performance of these models, and makes most quantities like measured "verbosity" and subsequent calculations of "intelligence per token" meaningless
Daily reminder that no one, including within academic AI research, AI engineers, normies, etc takes LLM sampling seriously enough.
The ban on these open models is coming within weeks, if not days. As usual, the excuse will be "national security".
For example: no government contract to any company who uses even one vendor in it's entire chain of dependencies, who uses such open models.
They can extend this further by laying more conditions, such as: any company dealing in this-this field can only use models "officially" approved as "safe". Rest you can guess how easy it would be to get that "safe" rating for such open models.
I'm not sure the outcome would be beneficial for the US as a whole here. But perhaps that is not their priority.
I claim the CCP will wise up within 2 years, possibly much much sooner, and ban their own companies from open sourcing to prevent the Americans from acquiring the capabilities.
Despite all the nonsense claims of China distilling US models, the reality is that the Americans absolutely do distill these free Chinese models, and distillation when full logprobs are available (i.e. you have access to the weights of the model) is an order of magnitude better than when you don't.
Yes, Chinese open weight models in the short term harm US closed source model providers bottom line. In the slightly longer term, "showing your hand" and publishing both the architecture innovations and the models weights will be too dangerous for the CCP to allow. This is triply true if they can release a model that beats the Americans on most benchmarks.
I've already warned investors that this is probably the closest open weight models will ever get to closed access.
https://www.businessinsider.com/xi-jinping-open-source-ai-us...
People on HN downvote objectively correct information because they don't like it 24/7. There's a reason the creator of Zig left and gave the computer version of a middle finger on the way out to HN!
commenting about voting is also something the HN guidelines warns against:
> Please don't comment about the voting on comments. It never does any good, and it makes boring reading.
I have to admit it rarely comes up in the coding tasks I usually give to LLMs.
But you already know that.
Any normal user is much more likely to ask questions to which the Anthropic and OpenAI models do not answer, than to ask questions about the modern Chinese history, to which a Chinese LLM will not answer.
This has been debunked here on HN so many times. The Chinese open models do answer the hairy Chinese political questions, and the raw APIs pass-through the response. Now, the answer might be blocked by the agent who's calling the API, specially if you are using a Chinese endpoint instead of the RoW (i.e. Singapore) endpoint.
That's the reason why you should always prefer a open agent/harness as well instead of using the provider's.
If you poke it just a few times, however, you get to the point where it will eventually say (paraphrasing) that basically only Israel, the US state department, and the ICJ say it's not a genocide.
That is to say that it's framing it as some sort of tricky complex question when it's not. And when interrogated, it basically admits that the only people who dispute it are Israel and it's supporters.
The majority of the world is religious - doesn’t mean the debate on religion isn’t a complex question.
The majority of the world approved of slavery historically.
The majority of countries have ethnically cleansed their Jews, many of them in living memory.
When interrogated you will find that the only ones asserting the war in Gaza is a genocide are people who were anti-Israel anyway.
I'm always suspicious that's the case given how mentions of gaza seem to bring out brand new accounts who only talk about Israel.
[1] https://quincyinst.org/research/the-eighth-front-inside-isra...
We are on a thread discussing Chinese models. Every discussion on here that’s negative about China or its models suddenly gets derailed via whataboutism to Israel/Gaza. A very convenient distraction.
And yes, we were discussing censorship of models which, as I pointed out, doesn't seem like ChatGPT is directly censoring data though it does appear to be manipulating it. Pretty on topic.
It was you, brand new account hiding your past opinions, who came in here to make this solely about Israel.
Yeah, I think you are likely a foreign agent. Prove me wrong and post from an established account.