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- Hacker News
- Why does the top card say "Intelligence #1/173" when the bar chart further down shows it only at position 7?
And the model isn't even shown in the speed bar chart just below. Such slop (the artificial intelligence website linked)
by croemer - Not clear to me how it selects that, but it considers it to be #1 out of 173 models "of the same class".by kzrdude
- Better than the latest Deepseek v4 Pro while being 3x cheaper in cost per task. Impressive!by jhack
- Can’t wait to try this out, and the only missing from this model for me is Image input supportby a012
- It has image/video input support (that is surprisingly good)by minimaxir
- Impressive. It kicked everything between itself and Sol xhigh out of the Pareto frontier. Can't wait to try it out.by AnodicElegy
- So how exactly is Anthropic and OpenAI ever going to pay back the trillions that they plan on spending?by m_ke
- Why do you think tech oligarchs have been cozying up to the Trump admin? They're angling for a government bailout, paid for by your tax money!by vrganj
- Its more Google Amazon Meta Microsoft who are spending trillions. They will be fine. So will Anthropic and OpenAI. Nvidia will presumably survive. The losses are all the real estate interests and contractors and contributory hardware companies etc.by applicative
- I expect they're going to fight each other to become the vendor of record for the government, and whoever wins will get bailed out. This is one area where they don't have to worry about competition from Chinese models.by yogthos
- Socialize the lost.They dont have to. You pay.by Haven880
- You could ask the same about how z.ai, moonshot ai, minimax, and alibaba are going to continue training and releasing models for free.by gruez
- > So how exactly is Anthropic and OpenAI ever going to pay back the trillions that they plan on spending?
It's really simple: if they truly get to human-level AI (or even superhuman AI), then money and debts no longer matter, since our current economic system will be obsolete. They are betting everything on this outcome.
I don't know if they will manage to do it before their debts have to be repaid, but considering the rate of acceleration in the past few months, there is a non-trivial chance that they will, IMHO. We will see.
by Marha01 - Looking at these numbers IMHO, with Gemini you get the speed what you pay for.
I have both GLM & Gemini in a subscription and see no reason for choosing GLM 5.3 Flash. Working with de speed of Gemini 3.7 Flash is such a delight that I accept the hassle of working with Antigravity CLI, coming from Claude Code which I use for GLM.Intel Cost lig per ence Task Speed Gemini 3.7 flash 56 0.40 338 GLM 5.3 flash 57 0.09 49 Factor 1 4.4 6.9by smartbit - I find the Time per Task[0] metric more helpful, because models vary enormously in the tokens required to complete a task. On Time per Task, Gemini 3.7 Flash is Matched with GPT-5.6-Sol, as well as on price per task.
GLM-5.3-Flash takes 7x (relative to Gemini and Sol) per task. So, it's cheaper, if you don't value your time! Don't value real-time workflows, don't value iteration speed, etc. So, doesn't seem very suitable for interactive or agentic work to me.
But having an ultra cheap model for async stuff is always very nice. (Still, the last few weeks feel less about tech and more like a contest between who can afford to give the biggest discounts!)
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I also like DeepSwe[2], although they measure Output Tokens and Agent Steps, which are misleading when one model has a much faster output speed. (e.g. on their metrics Gemini looks slower, because they don't account for that.)
[0] Time per Task - https://artificialanalysis.ai/?models=glm-5-3-flash%2Cgemini...
[1] Output Tokens Per Task - https://artificialanalysis.ai/?models=glm-5-3-flash%2Cgemini...
by andai - The analysis is still not compelling for me to switch from gtp5.6-luna to GLM-5.3-flash given
- costs per task $0.05 vs $0.09
- speed 130 vs 88
- where GLM has only 5 more intelligence point: at this point few point is meaningless for most of models
https://artificialanalysis.ai/models/comparisons/glm-5-3-fla...
Been using Luna exclusively since the price drop, and i've been very satified with all tasks from planning, writing code, and other agent tasks. (just change thinking level from low <-> ultra)
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btw, I did try out Ox Alpha, the coding feels good but still not way better for me to switch to it.
by yipinwong - GLM-5.3-flash is open-weight though. you can run it on your own hardware for a few k$. yes, it will probably be slower, but you're no longer reliant on a subscription, a working network connection, or the servers not being overloaded.by xnzakg
- I’ve been super pro-Luna lately. I really hope that Gemini-Flash-Lite is positioned to compete with it. We all know that Anthropic has abandoned Haiku and it would never be that cheap.
Probably shouldn’t say this here but I’ve been planning to up my $20/mo exploratory ChatGPT subscription to the $100/mo tier as soon as I hit my cap. Between the progress and quality of Luna and their continuous resets, it’s been a few months now that I’ve lived off the $20 tier, frankly waiting for the need to upgrade, credit card in hand.
I’m always trying new models, like many of us here, but the price is just so good for a well balanced, American, hosted model.
by vineyardmike - Which has a better monthly plan? Right now Z.ai "Pro" plan (the middle one) is $56/mo if you prepay for a year.
I signed up for their Lite plan when it was only $28 for the whole year (less than $3/mo). Definitely very happy with that purchase!
by BeetleB - > The analysis is still not compelling for me to switch from gtp5.6-luna to GLM-5.3-flash given ...
So Luna is competitive because a few weeks ago they did a 80% price drop?
Many here said that 80% drop was not a move against Anthropic but a move against chinese models and your comments indicate that's the case.
- I don't understand what would possibly make someone prefer speed over output? You'd rather get wrong bad answers that don't work as well very fast?
In general I really don't mind waiting 5, 10, 40 minutes. There's other things I can look at, other plans or assessments or outputs aplenty stacking up. Its baffling beyond words to me that anyone would take speed over good output. Surely the better output is going to save enormous time in the long run, have better outcomes. What is it that addicts people so much to speed, especially when the difference is between fast and very fast?
- Luna is at a very compelling point on the price/performance curve.
I have found that sometimes a smaller model with max reasoning is actually more expensive than using the next tier model with a lower reasoning effort. It’s certainly faster.
by psadri - Several factual errors about the model here. The input modalities are listed as text only, but the headline feature is image support. The context length should be 1048576 (so should GLM-5.3's, also wrong on the charts).by CGamesPlay