[–] gorgoiler 4 days ago
[–] asdf88990 4 days ago
[–] jacquesm 4 days ago
[–] dekhn 3 days ago
From a fair bit of coding with the agent, my experience with Qwen 3.8 (Qwen3.8-Flash-Next-GSQ-RCO-IQ3_S-0 on Strata, Qwen 3.8 27B on ninfer). In my particular case, I was trying to clone a recent HN post which allowed you to visualize how out of tune your singing was relative to a song, but as a web app or portable native app.
My experience is that both those models will generate an enormous amount of noise (literally: it was running audible unit tests on my machine to test the note-detection algorithms) while coming to a solution, if they do find a solution- while Claude (whatever the latest model is) or ChatGPT (ditto) will do 1/10th the amount of work to get the right solution. I suspect if I had the resources to run GLM 5.3, it would probably be significantly faster to get to a working solution than Qwen-3.8 27B, but likely still somewhat inferior to Claude or ChatGPT solutions, and also would generate a much larger energy bill on my part.
[–] spwa4 4 days ago
[–] morgoo 4 days ago
[–] spwa4 4 days ago
And at Q2, I think you're better of with Qwen3-coder-next on one DGX spark (or much better: on any apple silicon max, we are currently in the ridiculous situation that a second hand m1 max 64G will beat a DGX spark that's at least triple the price)
[–] cyanydeez 4 days ago
[–] wjnc 4 days ago
[–] snarfy 4 days ago
It reminds me that coin-op SF2 champion edition was like $6000 new, and you rented time with tokens. Eventually you could play a very good but more limited SNES version of SF2 at home for no tokens. And then PC hardware matured to the point where you can play the exact bits via emulator at better than original fidelity.
It will be very nice when AI gets to the emulator stage.
[–] doubled112 3 days ago
Do you think we'll be longing for the nostalgia hit of LLM models from 2025 in 2050?
Maybe we will collectively miss being completely right and inappropriate em—dashes.
[–] JacobLeeCadLaw 2 days ago
Those early GAN image generators were so weird that they produced art that felt genuinely creative. I don't know that whatever people are using to create modern Tung-Tung-Tung-Sahur instagram reel slop is even capable of producing similar things.
[–] pipes 4 days ago
(I'll run for cover now as I'm sure neogeo fans will disagree!)
[–] ASalazarMX 3 days ago
[–] MrBuddyCasino 4 days ago
[–] jonhohle 3 days ago
(I also adore MS)
[–] echelon 4 days ago
But also look at live service games and the shit modern game studios are doing to try to go back to the old world of rent seeking.
[–] senordevnyc 4 days ago
[–] doctorwho42 3 days ago
Game industry has first manipulated the economic conditions by restricting access to game content (skins, modding capabilities, always online drm, etc.) that previously was included in the price (buy game, you own that game outright).
Manipulation of public policy was a more recent thing with the laws surrounding underage gambling via 'loot-boxes'.
So I think the onus is on you to show us why these behaviors, which increase the wealth the companies are able to extract per game, are not rent seeking behavior.
[–] senordevnyc 3 days ago
As for the laws on underage gambling, countries all over the world are outlawing that, suing gaming companies, etc. The public is not in favor of underage gambling, and it's unclear to me how banning it increases the wealth of these companies? So I think the onus is on you to explain how this is an example of rent seeking.
[–] doctorwho42 2 days ago
Consider the use of microtransactions, battle passes, paid progression, and downloadable content. These systems often exploit the time, money, and emotional investment players have already made in a game. By deliberately slowing progression, withholding content, or introducing artificial scarcity, companies can encourage consumers to spend more money not because they are receiving a better product, but because they want to avoid frustration or access something they already value. The company is monetizing the player's existing commitment rather than necessarily creating new value.
This does not mean every gaming company or microtransaction is inherently rent seeking. Selling meaningful new content is a legitimate business activity. The criticism is that parts of the modern gaming industry increasingly prioritize extracting revenue from an existing player base over developing better games. When companies use their control over popular franchises and digital ecosystems to extract additional money from consumers who have few alternatives, they exhibit the very characteristics of rent seeking that economists criticize in other industries.
[–] senordevnyc 2 days ago
No, it’s not, you just made that up. Why doesn’t this match your previous definition?
The rest of your long AI-written comment has nothing to do with the principle of economic rent seeking.
Not sure why I’ve been wasting my time, but I’m out. Peace!
[–] zahlman 3 days ago
[–] behringer 3 days ago
[–] fsckboy 3 days ago
in the early days, 2 plays for a quarter was not unusual (but you couldn't buy one)
[–] LogicFailsMe 3 days ago
[–] InsidiousWombat 4 days ago
And the AI debt bubble price spike will probably stay there for a while.
[–] jauntywundrkind 3 days ago
Still (as bit over) 1/2 the ram bus width of a single HBM4 stack though! (1280b vs 2048b).
[–] jacquesm 3 days ago
[–] cyanydeez 4 days ago
Uber took a decade but eventually, the real cost of a taxi service went up for many use cases.
Your argument is only solid if we are headed to the singularity.
[–] doctorwho42 3 days ago
Perfect encapsulation of the problem. I may steal the wording you used for future conversations.
[–] otterley 4 days ago
[–] jacquesm 4 days ago
[–] glassresearch 4 days ago
[–] segmondy 4 days ago
[–] Gareth321 4 days ago
Now I want a local LLM server :( $25k is just so much money.
[–] ThunderSizzle 4 days ago
Sadly, the r9700 has gone up in price, but it's still the cheapest route. I use It on an old x99 Linux desktop and it achieves 50 tps decode and 1000+ tps prefill.
[–] Gareth321 4 days ago
[–] Jnr 4 days ago
Some censorhip and bias towards certain ideology is baked into those models.
While it is not a problem for programming tasks, I would never use it for certain other tasks.
[–] Gareth321 4 days ago
Self-hosting means being able to use abliterated models where the superficial instructions like not describing Taiwan as independent are burned off.
Censorship and bias are related but not synonymous. I agree that it's harder to remove political bias when the training data includes it. We know many of the frontier models are heavily trained on Reddit, for example, [which likely explains why we see such heavy left wing bias.](https://trakkr.ai/bias/findings)
More citations:
https://www.gsb.stanford.edu/faculty-research/working-papers... (article: https://news.stanford.edu/stories/2025/05/ai-models-llms-cha...)
https://www.tandfonline.com/doi/full/10.1080/29974100.2026.2...
https://ieeexplore.ieee.org/document/10817610
https://www.washingtonpost.com/technology/interactive/2026/0...
https://link.springer.com/article/10.1007/s11127-023-01097-2
[–] deepersprout 3 days ago
In open models you can "uncensor" them: https://arxiv.org/abs/2406.11717
[–] _ache_ 4 days ago
A lot more with Haiku equivalents (Qwen3.8 27B) or gemini. It's not frontier, but not that far away.
[–] Gareth321 4 days ago
[–] ali_chherawalla 1 day ago
[–] cft 4 days ago
[–] Gareth321 4 days ago
Worryingly, they're taking a walled garden approach, and they don't want to expose user data to competitors. After the monumental failure of Siri over more than a decade, I don't trust Apple to execute competently on AI.
[–] charcircuit 4 days ago
This is an alignment issue. OpenClaw with a local LLM with an email you setup for it could contact the police.
[–] Gareth321 4 days ago
[–] InsidiousWombat 4 days ago
[–] jacquesm 4 days ago
[–] Forgeties79 4 days ago
[–] bityard 4 days ago
Besides, I regularly see people here in HN spend a LOT more than that on hobbies and depreciating assets. A few years back, people with coastal salaries and tech jobs were tripping over themselves to spend $100k on a certain brand of trendy electric car.
[–] Forgeties79 3 days ago
[–] solyin 4 days ago
[–] Forgeties79 4 days ago
This is all this stuff that dries people to pay for frontier models. Even running modest models requires a few thousand, unless you just want really lean ones. People don’t need frontier but it’s not cheap to effectively run, say, a 16gb Qwen 3.6 or 3.8 in the 30b range. Ram is like $15/gb and GPU’s with 16gb vram are hardly cheap.
[–] sailfast 4 days ago
And what happens when the girl at the bar figures out that you TIMESHARE that Lambo?
[–] segfaltnh 4 days ago
[–] dekhn 3 days ago
My entire career has been based on purchasing the most hardware I could afford at home and using it near its peak. I've given up other life pleasures (dinners out, nicer car/housing) several times to max out my computational capacity.
Also hardware like this, if chosen carefully, often has a viable lifetime over 5+ years
[–] Forgeties79 3 days ago
[–] elevation 3 days ago
In case a future user wants to know what a 2026 model would refuse to do, I needed to rotate dozens of passwords last night both on the server and on the clients. When it was time to verify that the rotated credentials worked, I asked for a script that would rate limit the credential checks. Claude/opus5 (opus!!) refused and stopped in its tracks.
In another instance, Claude was making great headway bringing a legacy Windows app up in WINE until it’s saw “auth” somewhere and shut down. In the shutdown state, Claude asked me to reword the prompt to see if I could get it to act on less dangerous instructions. But when I reworded my request, narrowed the scope to be clearly unthreatening, or even redirected the model, it’s still rejected me. I suspect Anthropic uses the less suspicious rephrasing as training material to increase their rejection rate.
[–] latentsea 4 days ago
So much this. Plus everything else you mentioned. The freedom and control is real.
[–] dekhn 3 days ago
[–] ceejayoz 4 days ago
> I don't get to hear that it's not a doctor and I should call 911.
[–] mik1998 4 days ago
Anthropic has a significant interest in reducing liability, which in this case means mostly blocking this use case.
[–] ceejayoz 3 days ago
Unfortunately, it's fairly tough for someone to determine if they are themselves a reasonable person.
A model that only ever says yes is a cognitohazard, IMO. Like being a billionaire without the money to insulate you from the consequences.
[–] segmondy 3 days ago
[–] ceejayoz 3 days ago
Yes. I've also heard the cost (death) of people falling into pseudosciency rabbit holes.
[–] JTbane 3 days ago
[–] charcircuit 4 days ago
Local models can do this and with tool use they can even call emergency services for you on your behalf.
[–] sharmajai 4 days ago
[–] jack_pp 4 days ago
[–] segmondy 3 days ago
[–] jack_pp 3 days ago
Also, it's not like you're running any full models on local without shelling out 20k+
[–] jacquesm 4 days ago
[–] Asyakguen 4 days ago
[–] greesil 4 days ago
I've heard that there are legal software platforms like Clio that offer AI products, not sure what just eavesdropping on some lawyers at the bar.
[–] jacquesm 4 days ago
Companies pretty much give us the full overview of what they have from a technical perspective (and often much more than that), we sign NDAs with investors that have serious teeth in them. The data they share with us would not be disclosed under any other circumstance and even our reports are shared only with the clients.
It's a nice little business. I'm not going to risk offending my customers for convenience or to save some money.
[–] robotmay 4 days ago
[–] greesil 4 days ago
[–] tjwebbnorfolk 4 days ago
They are subsidizing all of us to the tune of $billions in losses per month. That can't go on for a decade. Probably not even for another 18 months.
I still use all the tokens Claude will give me on the max plan. But I also run deepseek v4 locally for overflow and for... contingencies.
[–] lelanthran 4 days ago
But, there is no need to make that bet - when prices increase, I'd look into renting a previous-gen GPU on a cloud provider. If the online GPU providers raise prices, then I would look into purchasing for on-site.
Until that happens, I'm not making any bets, because if all the token providers go bust GPU rentals are going to fall in price, and if they don't go bust after raising prices, I can still get years of GPUs for self-hosting at the price of a self-owned rig.
[–] tjwebbnorfolk 3 days ago
It's not economical today to run my own hardware, but the insurance is worth it to me in the sense that if my bet is wrong, I'm still okay with paying extra for the protection.
[–] calmingsolitude 4 days ago
[–] distances 4 days ago
[–] Gareth321 4 days ago
[–] latentsea 4 days ago
[–] petu 4 days ago
[–] pimeys 4 days ago
[–] latentsea 4 days ago
[–] MarcusE1W 4 days ago
(Of course this all depends on if their plans work out, but if not then the smaller local models will probably play a big role in the failure of their plan)
[–] murderfs 4 days ago
At API pricing (i.e. what all enterprise customers are paying), inference is profitable, even if they're paying usurious rates on cost of capital for capex. Where the frontier labs are getting screwed is that they're in a Red Queen's race with each other, spending tens of billions of dollars per year training the next frontier model, and not being able to recoup the investment on that model before it's obsolete.
That's why you see the CEOs calling for government intervention to "pace the frontier": it lets them reduce investment on training without risking that their competitors keep going and make them obsolete. Unfortunately for them, the Chinese labs exist, and would love nothing more than to take the frontier, so they're in a bit of a pickle.
[–] roca 4 days ago
[–] ThunderSizzle 4 days ago
However, that also means AI will be even more lobotomized since the cloud providers will panic over being liable
[–] root_axis 4 days ago
People keep repeating this, but it is only remotely close to true if you evaluate inference in a vacuum without any of the other supporting costs to facilitate that capability.
Just a few years ago people were saying the same thing about WeWork: "leasing is profitable, the unit economics of individual locations is net positive", and yet...
[–] m4rtink 4 days ago
- they raise the prices 10x
- go bankrupt
- ban you or your country
- decide not to help you with what you want to do for opaque reasons
- you are in jail because the model halucinated something and the company promptly reported you to the police
Better avoid all off these and go local IMHO.
[–] pixl97 3 days ago
Just note that your local model can 100% do this itself.
[–] ffsm8 4 days ago
The anthropic sub is likely still subventioned with VC money. So this may not even be available in 2 years.
But yeah, with current sub prices/budget... It's hard to go with anyone else unless you're rich.
[–] ffsm8 4 days ago
The anthropic sub is likely still subventioned with VC money. So this may not even be available in 2 years.
But yeah, with current sub prices/budget... It'd stick with it too
[–] reacharavindh 4 days ago
It doesn’t have to be black or white…
For my toy projects, adventures, learning exercises, and throwaway MVPs I will prefer the subscription plans… they are cheap for what they offer today.
[–] thaanpaa 4 days ago
It's training and tuning new models that cost them money. And that's why they are trying to scare people into thinking AI will kill us all in the next 5 years; they want bans on the open-weight models because they know they won't be able to compete with them.
[–] pimeys 4 days ago
If that is true, either the American labs are not optimizing correctly or they make a ton of money with inference.
[–] bityard 4 days ago
Hydro, wind, solar, nuclear, coal, they are building it all, as we speak, at least 10x more than the US. They are aiming to not just be energy independent, but energy dominant.
You can't now (and certainly won't in the future) be able to run an AI provider in the West as profitably as you can in China.
[–] GeekyBear 4 days ago
[–] tourmalinetaco 4 days ago
[–] cgio 4 days ago
[–] windexh8er 4 days ago
It's also very clear that providers are running variants of models, especially at the SotA levels. I wouldn't be surprised to find out at some point that 1-2 months after release OAI and Anthropic just run "good enough" quants to save themselves on inference (since they're losing money hand over fist). Another upside of local models is that I don't need to worry about model degradation at any given point.
[–] benoau 4 days ago
[–] dylan604 4 days ago
[–] jacquesm 4 days ago
[–] jacquesm 4 days ago
[–] gr_norm 4 days ago
Just think of how user-hostile other online services have gotten, and imagine how acutely painful the proprietary LLM providers could make theirs. Thankfully, open models provide some counterbalance.
[–] selcuka 4 days ago
Are you comparing to subscription prices or API prices? Because if it's the former it won't last forever.
[–] jacquesm 4 days ago
[–] pllbnk 4 days ago
[–] e12e 3 days ago
You say the big rig is 25k - and then the two sparks are about 1k each?
Electricity is for "just" the big rig?
[–] DanielHB 4 days ago
[–] bitexploder 4 days ago
My server can run Qwen Flash Next at 500 t/s aggregate (about 200 t/s single user). It's pretty great. I use it for local coding and all my worker agents. It is about as reliable as Sonnet 5 for agentic coding. I make 3D models, keep the home network and server updated, fully built ansible files.
You do NOT need 20K in hardware to run these models reliably. I built my own inference engine from scratch for fun. You can run Strata on 16-32GB cards at very respectable token rates if you have the standard RAM to go with it. I strongly encourage people to go use this model on OpenRouter and try it out for tasks.
I also have a somewhat lobotimized quant of GLM Flash 5.3 working and it's pretty decent too.
[–] jacquesm 4 days ago
I have 240G VRAM total which is a good reason why that rig cost as much as it does, and if I were to build it at today's prices it would be even more expensive.
[–] bitexploder 4 days ago
Kind of ironic, but it's the only way. I just really like this as an option. For a household LLM I have the IQ4_K_XL quant and plenty of capacity for everything you could want in a household LLM and it is trustworthy enough to not rm -rf /, etc.
And yeah that is a really nice amount! You can run and compose a lot of interesting models, vision capabilities. IDK. Plus this level of model is far more interactive in the sense that it can implement a well scoped ticket or unit of work but its not going to magically just figure some things out without guidance or a spec :)
[–] jacquesm 4 days ago
I tried getting some 170's when I first heard about that unlock but they were already unobtanium by then. That would have been a nice way to add a lot of VRAM.
GLM 5.3 runs pretty comfortably on this rig, even with large context.
[–] tepmoc 4 days ago
[–] hotelsacher 4 days ago
[–] bradknowles 3 days ago
I’ve always wondered about those models. Are we just sending all of our data over to China, instead of ChatGPT or Claude? Can we trust them any more than we do ChatGPT or Claude?
[–] bathtub365 3 days ago
[–] raven12345 3 days ago
[–] jamesfinlayson 4 days ago
[–] jacquesm 4 days ago
[–] jamesfinlayson 3 days ago
[–] Betelbuddy 4 days ago
[–] Shorel 4 days ago
At best they get a fine, and it will not make a dent in their cash reserves.
[–] Betelbuddy 4 days ago
But I was not even suggesting that, just run your local LLM on Cloud infra. Do you really believe they are ready to risk their Cloud business just to spy on your prompts?
[–] dmantis 4 days ago
[–] Betelbuddy 3 days ago
[–] dmantis 3 days ago
[–] tannertech 4 days ago
[–] jacquesm 4 days ago
Then again, I run a business and for the business it is absolutely manageable, it is roughly the price of a single job. Privately this would be a different matter but I assume that if you would do this privately you'd simply get a single (but powerful) GPU second hand and offload to RAM. Not as fast but with llama.cpp, 'ninfer', DwarfStar and various other clones of those two you can get some pretty decent performance out of single GPUs.
I've been buying powerful hardware since the 90's, starting with SGI and then ever larger Linux boxes. I make my living with them so it's never been a huge decision to invest some of the proceeds back into the tools. But on an absolute scale, yes, it is a lot of money.
[–] Eridrus 3 days ago
[–] larodi 4 days ago
[–] AndrewKemendo 4 days ago
I’m running local models more and more and starting to move to just tailscaling into everything
[–] lp92 3 days ago
What's your use case where the open models are working well?
[–] sjdh76 4 days ago
I mean IBM already has a track record of building gigantic amounts of garbage and over charging large corps and govts for it coasting on their brand name and networks to get deals. So using some cheap ass model fits their MO. Having used their shit mountain called websphere, what an IBM CEO says is not something I take too seriously.
[–] jacquesm 4 days ago
[–] sjdh76 4 days ago
[–] amelius 3 days ago
[–] dansquizsoft 4 days ago
I can't wait to use models that are 'slightly less good' when I am at work instead of something like Fable that lets me focus on the problem at hand as much as possible rather than also spending additional effort correcting for the tool I am using...
Over time NeoGeo realized they could sell you the hardware to play at home (“on-prem”) at arcade quality albeit at a price out of reach to most people. Alongside them, Nintendo and Atari gave you 80% of the fun at 20% of the cost. History will view games arcades as a flash in the pan compared to gaming at home.
Namco, Capcom, and Konami went into selling software instead of hardware but it feels hard to imagine buying a home copy of Fable** for $X,000 any time soon.
⸻
* That’s for video games. In fairground arcades you’d literally pay for tokens then use tokens for play. The analogy almost writes itself.
** The model, not the video game.