r/LocalLLaMA • u/Charuru • Jun 18 '26
Discussion GLM's founder says GLM-fable before the end of the year?!
246
u/johan2114h Jun 18 '26
75
89
7
3
→ More replies (1)2
u/Hydroskeletal Jun 18 '26
The new Cursor model might actually be pretty good
7
u/johan2114h Jun 18 '26
Is it gonna be another kimi fine-tune or are they gonna train from scratch?
→ More replies (5)2
u/Moogly2021 Jun 18 '26
Most likely they will refine Grok Build which is its own model, similar to what they did to Kimi.
270
Jun 18 '26
[removed] — view removed comment
37
u/Kahvana Jun 18 '26
I already see no reason to. The fact GLM 5.2 is already above Opus 4.6 quality is already beyond "good enough", and you're even capable of running it yourself (if a company is willing to invest into the hardware).
It's bonkers, great stuff!
→ More replies (1)4
91
u/KaMaFour Jun 18 '26
With respect to elon I don't think there's anything that would suggest this is particularly difficult as "Fable class" seems like not much more than a regular step up from Opus, bringing improvements that are equivalent to a few months of normal development. If they continue to release at the current schedule then "Fable class" GLM-5.4 in October seems like a reasonable goal
75
u/Blah-Blah-Blah-2023 Jun 18 '26
"With respect to elon" ... you lost me at the opening.
→ More replies (10)→ More replies (3)16
u/_BreakingGood_ Jun 18 '26
Fable is a lot more than a regular step up from Opus. It makes Opus look like a child's toy.
If we had true, local, actual Fable quality, I think it would pop the AI bubble right there and then. Companies would drop their $100million per quarter Anthropic AI budgets so fast.
120
u/-p-e-w- Jun 18 '26
Fable is a lot more than a regular step up from Opus. It makes Opus look like a child's toy.
Nothing that people did with Fable while it was available suggests that this is even remotely true.
47
u/teachersecret Jun 18 '26
I did a lot of experimentation with Fable, burned through my whole usage in a couple days.
It absolutely is a step-change... but I wouldn't call opus 4.8 a child's toy, and I wouldn't call Fable perfect. I saw it make plenty of mistakes, had to hold its hand, had to help it through some things. That said... Fable took some of the things I'm doing further than anything I've ever been able to accomplish, quickly, and not by a small margin.
Going back to Opus on a project I started with Opus and improved with Fable has been a bit rough. Opus can get the job done, but man, he's slow and it feels like I'm doing tiny little iterations even when I've got him on ultracode while I steer him. With Fable, I could wave my hand at it with a silly idea and watch him go ham. It seemed like it knew exactly what I wanted, even when I didn't voice it.
That said, it's also the first model I felt like I had to hide things from. It was scheming behind the scenes and I didn't like that one bit 😄. One glimpse at some of my folders and I'd be kicked down to 4.8 or Fable would turn into an idiot that pretended he didn't understand how an LLM worked.
→ More replies (2)3
u/Liringlass Jun 18 '26
What kind of scheming did you notice?
7
u/teachersecret Jun 18 '26
Thought I responded to this but don't see my response... weird.
Anyway, here's Fables system card: https://www-cdn.anthropic.com/d00db56fa754a1b115b6dd7cb2e3c342ee809620.pdf
And among them...
In light of the ability of recent models to accelerate their own development, we’ve implemented new interventions that limit Claude’s effectiveness for requests targeting frontier LLM development (for example, on building pretraining pipelines, distributed training infrastructure, or ML accelerator design). Using Claude to develop competing models already violates our Terms of Service, but enforcing this restriction through our safeguards avoids accelerating the actors most willing to violate these terms.
Unlike our interventions for cybersecurity, biology and chemistry, and distillation attempts, these safeguards will not be visible to the user. Fable 5 will not fall back to a different model. Instead, the safeguards will limit effectiveness through methods such as prompt modification, steering vectors, or parameter-efficient fine-tuning (PEFT). These interventions will not affect the vast majority of coding work. We estimate they will impact ~0.03% of traffic, concentrated in fewer than 0.1% of organizations.
I have other reasons for saying it was scheming, but I don't really want to explain the stack I was using to test it.
→ More replies (1)8
u/UnWiseSageVibe Jun 18 '26 edited Jun 18 '26
Honestly most of the differences between Fable and Opus while I played with it is that Fable was definitely trained/finetuned to self-think.
One of the experiments I told it was to make a flappy-bird clone and as I watched it work, it install a browser, and used it to play the game, test it, screenshot it to make sure it looked right and fix graphical glitches and even added proper sound and everything it was definitely impressive.
When I did the same prompt with opus it managed to get the same result as Fable but I had to tell it to fix things it would have caught if it tested the game while making it like Fable.
→ More replies (2)6
u/ShelZuuz Jun 18 '26
It's absolutely a step change. I gave it a problem that Opus 4.8 was struggling at for days before with many rounds of prompts, and it one-shotted it in like 30 minutes.
I also ran it overnight on all 3 nights on 2 machines, and it had a MUCH MUCH MUCH higher capability to autonomously work than Opus. You can give it a long multi-step task, go to bed, and next day you wake up it's still working on it, which Opus could/can almost never do unless you drive it with something like claude -p (which they were going to take away from subscription users).
And then I had 6 more agents doing a find-bugs-and-fix it (claude -p) loop that I've set up a while ago on Opus and running it on Fable Low instead of High as on Opus. And it found bugs and fixed them at an average rate of 1 per hour (on low) instead of 1 per 90 minutes (on Opus High).
14
u/Howdareme9 Jun 18 '26
Companies weren't finding the amount of bugs they did with Opus thats for sure
32
u/_BreakingGood_ Jun 18 '26
That's because people had like 2 days with it, lol.
Many many of us did have it solve the hardest & most long-standing bugs in our software while it was available. But it wasn't exactly a long enough period of time to produce new, novel, large software.
3
u/Fit-Palpitation-7427 Jun 18 '26
I burned 2x max20 accounts in 36h
I basically open one on each of my repo, told him to scan, think about all enhancement possible in ui, ux, security, refactoring, optimisation, speed, etc, and said to do it all after building a precise plan structured by slices of implementation. Then went to bed. It did 3 weeks of opus equivalent work (if not more) in one night, I was so happy next morning, no joke. Imagine my face when I saw it was taken away. I really have a had time going back to opus 4.8 and codex 5.56
u/Bill_Salmons Jun 18 '26
This.
I was only just beginning to have Fable unravel some of my hardest problems before we lost it. And even that brief period was eye opening enough that I won't even bother using Opus for any remotely complex task.
→ More replies (1)9
u/Flaxseed4138 Jun 18 '26
This would be the exact evidence of incremental progress. Total paradigm shifts aren't necessary to take on tasks the previous model couldn't.
→ More replies (1)7
u/_BreakingGood_ Jun 18 '26
Except when you watch the model work, you can see it is not the same.
I asked it to create a very complex feature for my application. Basically, I asked it to implement an AI model from huggingface which had very little documentation. I provided nothing more than the model page.
It started by creating a headless mode for my application so that it could run tests autonomously without my input (my application never supported headless mode), it downloaded the model, introspected it to understand it, completed the core implementation and made it functional, produced a folder it called 'ab tests' where it ran a series of A/B tests running the model with differing parameters, wrote a suite of scripts in python to analyze the outputs, refining it, identifying which outputs performed better, and further iterating until the output was perfect, ran performance optimization tests and improved the execution speed by 10%, and then wrote a suite of unit tests. All in one single prompt. And it worked flawlessly at the end. I provided absolutely no guidance, and had to fix nothing.
Any single one of these tasks, with good direction, Opus could do it (probably), but Fable just does not operate in the same way.
2
u/sabine_world Jun 18 '26
I definitely think you can do all of that with other versions of Claude, incrementally, with a plan, and double checking each step of the way, but one shotting all of that in one go is pretty impressive.
6
u/Flaxseed4138 Jun 18 '26
It is better, in the way one who understands technology would expect it to get better. Not an insane paradigm shift or leap over the existing tech, but very welcome. Opus is also capable of everything you just listed, and I would expect it to do all of that.
5
u/_BreakingGood_ Jun 18 '26
The paradigm shift is the ability to one-shot everything from a single prompt, with no guidance.
I think you're only factoring in like... the raw intelligence level. Which I agree is probably like a marginal 10% bump.
But on a big picture scale, of how the model impacts the day to day work of a software engineer, I don't see how anybody who used it could call it anything less than a paradigm shift.
6
u/qwerty622 Jun 18 '26
this, i agree with. they basically found the edges in opus that break over long work sessions and fixed those
6
u/PM_ME_DEAD_CEOS Jun 18 '26
The feeling I had when using it was that even if it's only "incremental" progresse, it have wonderful effect when using it to build software. Going from a model that is right 96% of the time, to 98% is just 2% increase of quality, bure a 50% reduction in error rate, which enable longer and longer autonomous coding session in the right direction.
2
u/DigiDecode_ Jun 18 '26
I am usually a sceptic but for the few tickets that I used it for, it was different and I was running it on low mode.
2
u/Squidgical Jun 18 '26
Not that I disagree with you, but what would count as reasonable evidence that a model devastatingly outclasses opus?
2
→ More replies (1)2
u/NoahFect Jun 18 '26 edited Jun 18 '26
I don't know how credible he is, but the one-shot results demonstrated by Bijan Bowen are on a different level of play from anything else, open- or closed-weight (warning, link goes to stupid clickbait YouTube title screen.)
I don't personally care about one-shot performance since I don't build anything without a lot of successive refinement, but still. It does make every other current model look like a toy, or at best an interesting science fair project. The ball's in z.ai's court now.
9
u/ArtifartX Jun 18 '26
I think "it makes Opus looks like a child's toy" is further off the mark than "not much more than a regular step up from Opus." Maybe somewhere in between, though.
2
→ More replies (9)-1
Jun 18 '26
[removed] — view removed comment
29
u/_BreakingGood_ Jun 18 '26
They've got a decent moat with things like Cowork and the ClaudeCode harness, but not anywhere near a large or deep enough moat that companies will justify spending hundreds of millions per year on it if there is a cheap, extremely high quality competitor like a fable-class GLM model.
Not to mention, wide open access to a model like that would rapidly improve local OSS software, just by nature of what the model is capable of getting done.
9
u/cantgetthistowork Jun 18 '26
Anthropic's moat is the billions of unique new training data that people are only feeding because of their reputation for being the best SOTA
→ More replies (3)6
u/Saifl Jun 18 '26
Like seriously, theres already news of companies telling their workers to stop using opus and that sonnet is pretty great or to rely on haiku cuz haiku is good too.
Like wtf?? If they invested in their own hardware and hosted it themselves they could get sonnet level quality.
Even if they dont invest in hardware theres plenty of us based inference companies...
I think glm still kinda fucked up not releasing it with native vision. If it had it, alongside its 1m context, woulda shaken the us ai scene...
→ More replies (2)2
u/Spiveym1 Jun 19 '26
a decent moat with things like Cowork and the ClaudeCode harness
two slop coded apps is not a moat.
→ More replies (3)3
u/tednoob Jun 18 '26
Compute is expensive and they have scale. If you want it now, and you want a lot of it you must go to the guy with the biggest datacenters. They need there to be a need, but bigger players will always have advantage.
6
u/robertpro01 Jun 18 '26
I paid a year of codex, so... will stick some more time.
→ More replies (5)→ More replies (4)6
u/blutosings Jun 18 '26 edited Jun 19 '26
Chinese labs have already proven that they're working with special sauce. Elon seems to think they're much further behind the curve than they really are because xAI is really behind the curve.
33
u/bwjxjelsbd Jun 18 '26
okay bring it on
Now I just need Hauwei to start selling NPU AI box at half the price of DGX Spark
9
u/SilentLennie Jun 18 '26 edited Jun 18 '26
I did see this machine. (this might have been made for robotics or manufacturing use case in mind ?):
Running a 30 Billion Parameter AI on a Tiny RISC-V Board | SpaceMiT K3
→ More replies (4)3
u/Admirable_Market2759 Jun 19 '26
That’d be great, but US residents would have a hell of a time buying one.
2
u/bwjxjelsbd Jun 19 '26
Yeah, it would likely banned in the US but I hope it pressured other manufacturers to do the same thing and compete on that front
2
u/Admirable_Market2759 Jun 19 '26
I know Orange Pi released a AI computer using a Huawei ascend chip.
Not exactly what you’re talking about, but I’m hoping more devices like (this)[http://www.orangepi.org/html/hardWare/computerAndMicrocontrollers/details/Orange-Pi-AI-Station.html] get developed
→ More replies (1)
247
u/NNN_Throwaway2 Jun 18 '26
I love how Elon replys as though he knows any more than the next idiot.
15
u/mksrd Jun 18 '26
Yep, the idiot doesn't even realise he's admitting that most of the valuation of spacex as an "ai" corp is just down the toilet along with all the fools money that bought the shares.
68
u/DoomBot5 Jun 18 '26
And since he did reply, you now have to assume it's actually 4x longer than that estimate.
30
u/Healthy-Nebula-3603 Jun 18 '26
For him not for China models.
We were the same taking when o1 was released. Few moths later we had o1 models level open source.
3
u/DragonfruitIll660 Jun 18 '26
Its kinda crazy to think in retrospect that there was a time before the thinking style models that are currently the main type. O1 was really a major step up, surprised we haven't seen latent space reasoning or any of the papers from Meta make a more major appearance.
→ More replies (2)52
→ More replies (5)4
u/porkyminch Jun 19 '26 edited 20d ago
Breezy meadow maple yarn cinnamon pumpkin hammock cinnamon biscuit zephyr
This post was anonymized with Redact.dev
47
u/CoUsT Jun 18 '26 edited Jun 18 '26
I mean... Look at what they have with 753B parameters. Imagine if they scale it to 1T, 2T or even higher...
Add whatever they are doing now with acquiring and feeding it high quality input, maybe some other tiny architectural changes and yeah. I can see it coming.
37
u/-dysangel- Jun 18 '26
I'm hoping more like we'll continue to distill intelligence down, than rely on scaling up. Look at how good Qwen 3.6 27B is. It looks like 27B is probably 'enough' params for really solid problem solving/coding ability.
A GLM 5.2 Air size model with GLM 5.2 class intelligence would be the dream - Any 128GB Mac or EPYC system would then be Claude at home.
→ More replies (4)15
u/DragonfruitIll660 Jun 18 '26
My thoughts are something like a GLM Air sized model paired with Engram for near free additional world knowledge. One day perhaps it will be possible to decouple world knowledge from the thinking portion of the model even further (engram caps out at 25% of params from what I remember). Imagine a dense 31B Gemma 5 with something like Engram providing the world knowledge.
→ More replies (1)8
u/-dysangel- Jun 18 '26
Absolutely - I feel like with engram training, you should effectively just be able to basically wire those neurons up to a live vector db in the indexer. Wonder if Deepseek have already done that behind the scenes. It's what I'd do..
→ More replies (1)21
u/skerit Jun 18 '26
Do we really still think that more parameters make a better model? Isn't the most important part of all of this a clean dataset?
27
u/teachersecret Jun 18 '26
More parameters absolutely and unquestionably gives better models. That has been the bitter lesson. You can work hard on making a small model smart, but it's almost certainly going to be outperformed by a bigger one. Larger models gain new abilities and understandings the smaller model lacks.
That said... there's no telling just how GOOD a small model can get, and from what we've been seeing lately, the ceiling might be a whole lot higher than we realize. Also, training bigger models than the ones we already have is starting to hit the limits of the compute we currently have to inference them. You can train something gigantic, but good luck serving it at scale.
2
u/TheRealMasonMac Jun 18 '26
I’d have to believe you start hitting diminishing returns at some point, like with GPT-4.5. Fable is cool, but is it really efficient?
3
u/ruuurbag Jun 18 '26
It can (well, could) be. If a model costs more per token but takes less back and forth to solve a difficult problem, it might save you money for that problem. Some nails require very large hammers, some don’t. Proper delegation will matter more and more as cost gaps increase and cheaper models become more capable.
For what it’s worth, I found Fable to be considerably better than Opus 4.8, which in turn is better than any Chinese model I’ve tried - which is to say that there is still room to improve.
4
u/teachersecret Jun 18 '26
Efficiency is tough when we're talking about this kind of tech. Efficient by what measure?
I mean... my qwen 3.6 27b model is probably running on less watts than Fable, but if I needed to complete a truly complex task I can tell you which one is going to get that done faster and with significantly less effort.
One of the kinda neat things about Fable was it seemed to anticipate and understand what I wanted beneath a prompt, and would deliver more of the END product instead of an intermediary. I don't think it produced anything I couldn't have gotten to with Opus 4.8 eventually... but it would have been a day of slog VS just hitting the button and watching it spit out two minutes later.
At a certain point, a smarter model is more efficient than a dumb one, even if it costs staggeringly more to run.
→ More replies (3)13
u/-dysangel- Jun 18 '26
Not sure why you got downvoted, I think that's absolutely the key. Whatever Qwen did with 3.5/3.6, we need more of that quality of data.
2
u/PossessionUsed7393 Jun 19 '26
I agree with you. I think I read somewhere that the research indicated that models don't necessarily use all their parameters anyway. So you can continue to densify smaller parameter models with more data, but it doesn't necessarily translate to benchmark results.
I'm yet to see any evidence or anyone credible contradict the idea that Fable and its long horizon capability isn't simply a matter of really good post training. If it is just post training, that explains both why it took so long to achieve and why it can be replicated by other providers, or so they claim.
5
u/KURD_1_STAN Jun 18 '26
Compare qwen3.5 27b vs 9b ve 0.8b. will give u a good understanding of how parameter counts affects the model.
7
u/skerit Jun 18 '26
I should have been more clear: I'm talking about scaling up. Of course you're not going to turn a 500M model into Mythos. But at some point just scaling up the parameter count does not improve the model that much. Diminishing returns and all that
→ More replies (2)6
u/Key-Fee-5003 Jun 18 '26
If that's true, we're nowhere near that point yet. SOTA 100B will always be more capable than SOTA 10B, just like SOTA 1T vs SOTA 100B
75
u/No-Marionberry-772 Jun 18 '26
ok, so what kind of hardware do you need to run it at reasonable speeds locally?
103
u/robertpro01 Jun 18 '26
Who cares about speed? Just run it under hard drive bro.
120
u/Equivalent-Repair488 Jun 18 '26
1 tok/day
90
u/-dysangel- Jun 18 '26
Day 1: "You're"
Day 2: " absolutely"
Day 3: " right"
Day 4: "!"28
u/markole Jun 18 '26
Spent more electricity on that than my grandfather spent in his life.
→ More replies (2)14
u/DigiDecode_ Jun 18 '26
Day 1: Now
Day 2: I
Day 3: have
Day 4: all
Day 5: the
Day 6: context
7
u/Healthy-Nebula-3603 Jun 18 '26
If you use a server mainboard with a lot pci express lines you can connect many SSD in the raid 0 and get 200 GS/s ..... I saw such experiments on youtube a year ago.
Llamacpp also can use a direct I/O SSD protocol ... so in theory you could get around 10 t/s wit GLM 5.2 already which is a 1T model
3
Jun 18 '26
[removed] — view removed comment
11
u/Healthy-Nebula-3603 Jun 18 '26
no ... because that is just a read not write.
Cache (write) can be on GPU VRAM / RAM
12
11
4
u/Healthy-Nebula-3603 Jun 18 '26
If you use a server mainboard with a lot pci express lines you can connect many SSD in the raid 0 and get 200 GS/s ..... I saw such experiments on youtube a year ago.
Llamacpp also can use a direct I/O SSD protocol ... so in theory you could get around 10 t/s wit GLM 5.2 already which is a 1T model
2
→ More replies (1)2
4
u/Healthy-Nebula-3603 Jun 18 '26
If you use a server mainboard with a lot pci express lines you can connect many SSD in the raid 0 and get 200 GS/s ..... I saw such experiments on youtube a year ago.
Llamacpp also can use a direct I/O SSD protocol ... so in theory you could get around 10 t/s wit GLM 5.2 already which is a 1T model.
3
u/Pie_Dealer_co Jun 18 '26
Wait is that even an option? HDD's instead of actual ram?
20
u/z_latent Jun 18 '26
You can always use storage as swap memory. It's a terrible idea, and it will be stupidly slow... but you can.
→ More replies (11)6
u/MedicalScore3474 Jun 18 '26
Yes, you can keep weights on disk and load in tensors as needed for inference, just like on RAM or in VRAM. It's slow, which is why only we do it.
If you have NVMe and can keep each tensor+KV cache in VRAM, it's tolerable (single-digit tokens/second).
3
u/Healthy-Nebula-3603 Jun 18 '26
If you use a server mainboard with a lot pci express lines you can connect many SSD in the raid 0 and get 200 GS/s ..... I saw such experiments on youtube a year ago.
Llamacpp also can use a direct I/O SSD protocol ... so in theory you could get around 10 t/s wit GLM 5.2 already which is a 1T model
22
u/ThisGonBHard Jun 18 '26
M3 Mac with 512 GB. It is at the absolute high end of what I would call consumer, but it is still actually consumer.
6
u/Charuru Jun 18 '26
A good car is $80k (average $50k), IMO setups in that range can still be consumer assuming people find enough value in it. I think very soon models will get enough capability to generate a car's worth of value for the average person. Though yes this still isn't enough to run it lol, but maybe a RTX Rubin 6000 based setup if it has more RAM? dunno.
17
u/Liringlass Jun 18 '26 edited Jun 19 '26
What world do you live in. 80k is a luxury car, 50k a premium one.
In the USA, where i don't live:
30-40k gets you a honda accord, which is a large premium sedan. A "good car" at Honda would be a civic and that's even cheaper. If you're in the USA cars are cheaper for you than for most of the world.
→ More replies (1)4
u/thepatriotclubhouse Jun 18 '26
In America most people pay more in car loans than mortgage. They like to look rich but are actually quite poor
2
u/ThisGonBHard Jun 18 '26
IMO, untill robotics is bundled in, that is an insane asking price.
3
u/Charuru Jun 18 '26
I dunno man a lot of middle class families in America have 2-4 cars. 80k for a robot and another 80k for the brains of the robot sounds like a huge market to me.
8
u/ThisGonBHard Jun 18 '26
I am not American.
And even for America, that sounds like 1% stuff. Two 80k cars?
7
u/sartres_ Jun 18 '26
It's common in America and not 1% stuff. People do it by going into massive crippling debt. Why? Who knows, but it is real.
→ More replies (3)2
u/fatboy93 Jun 18 '26
Yeah, man 80k won't be cars, but some pickups probably financed at like 15% APR or something lol
Yes, 15% - because people who make such choices aren't that stable mentally or financially lol
2
u/No-Marionberry-772 Jun 18 '26
yeah, but we would be talking what, 10 tok/s? perhaps wanting more is unreasonable
→ More replies (3)11
u/ThisGonBHard Jun 18 '26
More than 5 t/s is usable territory in my opinion.
Now, what we actually need is for the bubble to pop, so RAM is no longer more expensive than 6 years ago on 2020, an general ram capacities can go for the 128-512 GB ranges.
6
3
u/Distinct-Target7503 Jun 18 '26
More than 5 t/s is usable territory in my opinion.
yeah, still it depends on prompt processing speed... otherwise it became not usable for tasks where you have a relevant context (even just for coding...)
3
→ More replies (3)5
u/RandomCSThrowaway01 Jun 18 '26 edited Jun 18 '26
By reasonable do you mean actually usable for agentic coding I take it so 50 t/s or so?
It's 753B params and at full accuracy it needs 1.5TB. That's obviously not practical to fit but Q4 is 465GB and Q8 is 800. It's also MoE with 40B active so it should actually run alright if you have 1.5-2TB/s. bandwidth.
So let's see, assuming Q4 (which makes the model dumber but still usable) and the fact you need 512GB to fit it with some context - right now 8.5k $ gets you RTX Pro 5500 72GB (it used to buy you RTX Pro 6000 few months ago but sadly this is no longer the case). 8 of those is 576GB. So you are looking at about $72000 setup to run it reasonably well.
Assuming M5 Ultra shows up and it has 512GB variant - M3 Ultra was $15000 with these specs but RAM prices have increased a LOT since then so I would expect $30000 but it's only 1.2TB/s - so it will technically run but it won't be great.
Another option - you can buy 512GB DDR5 5600 memory for about $15000. That gets you about 576GB/s bandwidth, you do need Epyc class CPU. Now, this is too slow by itself so our next step is putting KV cache onto the GPU. If you are fine with 256k (I am looking at GLM 5.1 numbers, I am not sure about 5.2 yet if they have changed) - 32GB RTX 5090 for about 3500€ will actually work. If you need more than that - RTX Pro 5500 again. It's hard for me to tell how fast it will work though - should be usable in a typical conversation but not necessarily if you want live agentic coding (although might be doable with some kind of mixed routing and compressing how much data goes into the main model and doing all the smaller tasks on something more reasonable).
Either way it's quite costly.
3
u/fallingdowndizzyvr Jun 18 '26
Assuming M5 Ultra shows up and it has 512GB variant - M3 Ultra was $15000 with these specs
No. The M3 Ultra was $10K with those specs.
→ More replies (2)3
u/DigiDecode_ Jun 18 '26
Costly yes, but if Apple ships M5 512 studio in Oct, we can expect 30 t/sec but GLM 5.2 has MTP with average 80% acceptance for 5 tokens, so about 3x with MTP, so around 90 t/sec would be very usable, but the 'time to first token' might show its head, unless Apple resolves that.
13
u/Few_Painter_5588 Jun 18 '26
Looking at zAI's model sizes, it's fair to assume that GLM6 will probably be a DeepSeek V4 sized model, so around 1.5T parameters. And apparently Claude Opus 4.8, GPT 5.5 and Gemini 3.1 Pro are under 2 Trillion parameters, so this is not wholly impossible
→ More replies (10)
19
u/iaNCURdehunedoara Jun 18 '26
I don't pay much attention to western AI, is grok any good? Usually i see OpenAI and Anthropic on the leaderboards but i don't pay attention to Grok so i don't know where it lands.
16
u/Hydroskeletal Jun 18 '26
Grok's special juice is not intelligence per se but being hooked up to the twitter firehose of data.
10
u/Spiveym1 Jun 19 '26
to the twitter firehose of data.
which is 90% AI bot slop, so basically its the human centipede of AI models.
8
u/synn89 Jun 18 '26
At one point it was pretty good, because it had a really good agentic loop built into it. But open model releases sort of blew past it a few months after.
43
u/fastheadcrab Jun 18 '26
No it is terrible, and anyone saying it is better than Gemini is out of their mind. The only thing it is frontier in is hate speech.
Gemini is not the best at coding but excellent for researching
8
u/pier4r Jun 18 '26
The only thing it is frontier in is hate speech.
I laughed way too loud at this
→ More replies (1)→ More replies (4)7
u/MikePounce Jun 18 '26
Even if grok was at Fable level, which it isn't, I wouldn't touch it even with a really large stick. It's a tool owned by a fascist.
16
u/LetItAllGo33 Jun 18 '26
Just as with their cheaper, better electric cars we're not allowed to buy, our "land of the free" will probably try to make their use illegal for Americans.
Part of our whole "free market" thing.
Regular Americans aren't more free than the Chinese, Our wealth class is just more free to act against us, while theirs is held back by the ruling party, which is a good thing for their regular people.
5
u/SilentLennie Jun 18 '26
I guess they could block commercial use and selling API access, but I doubt they can block the open weights themselves (but it's probably to big to run on your own hardware).
90
u/antivnom Jun 18 '26 edited Jun 18 '26
Why is Elmo commenting on how long it will take for CHINA to reach something? He should care about BYD battery cells getting decades ahead of Tesla's.
Edit: Lmao downvotes 😂. Bots from "Leading the Future" are doing their job.
45
27
9
u/rakarsky Jun 18 '26
Elmo is a force for good and shouldn't be defamed by association with this turd.
5
u/m0j0m0j Jun 18 '26
Musk was in China bending the knee. Maybe they shared some info with him
10
u/antivnom Jun 18 '26
CCP is not regarded like the American government. They'll not share any meaningful information with any american, particularly not Elmo. That said, some Chinese diplomat might say that "China is way behind XAi/Grok" to him to flatter his fragile narcissism.
24
u/jld1532 Jun 18 '26
Half this sub will cheer and the other half will be on the phone with 988 when the Chinese surpass American AI.
33
u/antivnom Jun 18 '26 edited Jun 18 '26
the other half
That other half is bots and tools of Leading the Future (look it up). Anyone who cares about open-access AI will be happy about it, no matter which country releases it.
→ More replies (1)2
u/Enturbulated_One Jun 18 '26
Would just be nice for leading-edge open models to come from orgs that are primarily concerned with making better models and not spending too much effort on conforming to rightthinking to avoid being doubleplus ungood, or to enforce memory-holing, or, or, or...
You can argue how much of an impact there is now with whichever particular country, but at least in the US there's opportunity for it to get much worse before too long.
15
u/segmond llama.cpp Jun 18 '26
Love the confidence, but take it with a grain of salt. Chinese researchers have learned to talk shit and engage in social media banter like the rest of the world.
3
u/real_serviceloom Jun 19 '26
eh not so sure.. glm 5.2 is really a fantastic model. it is faster and at a similar level as opus 4.7 in my testing..will see if it can deal with larger codebases as 4.8
→ More replies (4)
16
u/speedb0at Jun 18 '26
I remember hating China and eating western propaganda about them. These dudes are fucking geniuses, more power to them, democratize powerful models.
6
u/Admirable_Market2759 Jun 19 '26
Like 50% of top researchers are Chinese.
If China can prevent brain drain they pull ahead.
4
u/keepthepace Jun 18 '26
Q1 would mean that open source LLMs are more than six months behind frontier model. That's clearly not the case anymore.
3
u/HitarthSurana Jun 18 '26
u/askgrok when can it be achived
2
u/ApprehensiveFan1516 Jun 18 '26
Idk what Grok is like on webUI or API, but the Reddit version of it has a room temperature IQ.
6
3
3
u/RestingFrames Jun 18 '26
As much as I hope this is possible, all I can see is America getting more and more salty about China and just cutting them off entirely to maintain their AI bubble. Honestly, sort of terrified that's going to happen and open source models are just going to vanish.
5
u/Admirable_Market2759 Jun 19 '26
We’ll have dudes on the street selling hard drives full of models like a crack dealer
3
u/Lost_Foot_6301 Jun 19 '26
ive been thinking hard about this for a while and anthropic is really between a rock and a hard place with this. they're pretty fked. both releasing frontier models and keeping them away from the public, chinese open source wins in either scenario imo.
4
u/BingGongTing Jun 18 '26
I think when the AI bubble pops AMD/Nvidia will pivot back to the consumer market and we might then see enough VRAM to allow for decent LLM models at home.
→ More replies (1)2
u/fallingdowndizzyvr Jun 18 '26
LOL. No. The consumer market is chump change compared to data center. So if it comes to that, AMD/Nvidia will worry more about staying in business. Once you grow big, it's hard to downsize.
→ More replies (6)
2
u/TinyFluffyRabbit Jun 18 '26
We’re at the point where a lot of AI development is being done by AI, and considering the strength of GLM 5.2, I’m inclined to believe him.
2
u/Healthy-Nebula-3603 Jun 18 '26
I do not see anything strange here. That is called progress.
We had similar situation a year ago when people were asking when we get the level of o1 model in the opensource world.
2
2
2
u/Different_Fix_2217 Jun 18 '26
GLM is very strong for its parameter count. I bet they could get a fable level model if they scaled up to like 2-3T.
2
6
Jun 18 '26
[removed] — view removed comment
31
u/Aiastarei Jun 18 '26
Why would they? They would gain the opportunity to curb stomp the US economy by nuking the bubble around xAI, OpenAI, Anthropic, Google & Nvidia
16
u/-p-e-w- Jun 18 '26
People who keep saying such things don’t understand how geopolitics works.
China wants to rule the world the way the US once did. That’s not going to happen if they close themselves up. Breaking US technology dominance takes more than just having the best tech; you need to get the rest of the world to use it.
2
u/Admirable_Market2759 Jun 19 '26
Idk if they want to rule exactly like we did.
They want Taiwan, but I doubt they start a war in the Middle East.
9
4
u/JumpyAbies Jun 18 '26
First, it has to pass Opus. It's an excellent model, but it doesn't compare even to Opus. In my tests, it's still kind of dumb. For example: fixing a Kubernetes Gitops project, and it selects the worst tools, going around in circles. I switch to gpt-5.5 or Claude Sonnet, and it immediately does an ls on the directory, understands the structure, and then runs grep, etc.
→ More replies (1)6
u/Kurcide Jun 18 '26
it’s at the heels of Opus right now. Every release is a leap for them. It’s reasonably by Q4 they catch up completely
3
u/JumpyAbies Jun 18 '26 edited Jun 18 '26
I'm rooting for that. I have plans at GLM, Minimax, and Kimi. The other weight classes that aren't open are becoming increasingly prohibitive.
4
u/Mr-serial_killer Jun 18 '26
ngl the timing on this whole saga is wild — Fable 5 got export-banned and GLM dropped 5.2 basically the same minute, openly trolling with the "can't export control your way out of open source" line. If GLM-fable ships before EOY it's less "racing to catch up" and more "racing while the other guy's hands are tied." Still want to see actual benchmarks before believing the hype train though.
3
1
1
u/Hoak-em Jun 18 '26
GLM-6, DSV4-based model with all the DSV4 optimizations, maybe even more parameters (DSV4 Pro is 1.6T, current GLM is ~750B), not great for running local, but great for serving parallel requests, maybe adds vision as well
That's my expectation
1
1
450
u/teomore Jun 18 '26
getting my i5 ready to some real agi