I have taken another look on these open models after the fiasco of Fable and GPT 5.6 this weekend and... GLM-5.2 truly is a good workhorse model for daily programming. I consider myself a heavy user of LLMs and a seasoned developer. A typical session for me with GPT is usually over a hundred dollars...
This weekend I programmed a matrix bot with encryption and a Rust agent with some tools. Because I need one and OpenClaw just felt... not what I wanted. Two days later and 20 dollars poorer I have what I need: a multimodal agent written in rust that has access to my homelab.
Nothing felt off with GLM. It did what I wanted, was fast, had a decent not very annoying personality and was much cheaper than Opus or GPT.
I used it unquantized through Fireworks, but there are multiple other providers too.
If you're using Matrix, consider Hermes as a harness if you haven't already. Native gateway support. I've been primarily using mine through Element and it has largely been great.
Oh interesting. I basically chose Matrix because setting anything up with Whatsapp or signal was kind of painful and telegram doesn't make it easy to use encryption with bots.
I kind of wanted to see if I can make a Matrix agent from scratch with Rust with GLM and it was surprisingly easy. Just make something for myself how I want it. Maybe I'll take a look on Hermes later...
8 X RTX6000. It will run you around 80-100k to get started with a model at this size with decent tps..
Don't worry though, open source evangelists will tell you that these will be running on your phone in the next 3 years.
For $100k you could run this model 24/7 through open router with 10 concurrent sessions at 50tps for a decade and have money left over for a vacation. There's no point in investing this type of money in local models unless you have a business where you're already paying for many employee's individual token usage.
Depends how much you value privacy and running uncensored models.
Personally, I’m waiting for hardware to hit the secondary market before I buy something to run unquantized models like GLM. But I have no doubt that I will, at some point.
You can run the NV4FP quant with 8x RTX6000 cards at 50-75 tps output, but not (practically speaking) the OEM FP8 version. You will learn more about PCIe than you ever wanted to know.
The real gangstas are running 16x RTX6000s. Too rich for my blood, and the NV4FP quant doesn't seem to be that much worse.
Yeah, the neoclouds and hyperscalers are taking massive losses right now, self hosting is basically signing yourself up to do the same. There are philosophical reasons to do so but it’s a terrible economic decision
Sure, If you want to light money on fire for entertainment, more power to you. There's probably worse ways to light 100k on fire. If I have an extra 100k laying around it's going to my family though.
Would you be better off pooling that money with some hackerspace group and then setting up shared inference infra, so that way you at least get better utilization?
Claude code it's the only way to get access to the actual amortized cost of running a Claude-scale model. The consumer non-enterprise API is extremely expensive (with increasing marginal costs for the user and fat profit margins for Anthropic). If you want to approximate a State level attacker's cost where they can have the model on their own hardware, Claude Code is probably the best guess at the amortized cost.
These numbers are seem pretty low compared to what I was able to achieve specifically around windows kernel, win32k<->win32u to be exact. It honestly wouldn't surprise me anymore if china started surpassing models that US makes public, at least in specific categories such as cyber.
GLM 5.2 is already capable enough to assist in self-training which is similar to what we saw happen with frontier models and they appear to be getting there at a significantly lower cost than openai/anthropic.
If that happens it'll be an absolute disaster. Imagine a scenario where Anthropic and OpenAI prohibit most US companies from using their latest models because of safety.. And meanwhile attackers use equivalent open source models to attack US companies.
Any prohibition on open source models will do nothing to fix the problem.. since attackers will never feel bound to the law. All advanced models must be available for defensive purposes.
Right, but is there any evidence of intelligence behind any of these (government) decisions? It’s just regulatory capture + marketing (plus some people living out an imaginary fantasy that they’re in Neuromancer or something), absolutely no reason to think they won’t try and target open models as part of this.
> since attackers will never feel bound to the law.
But that's the whole point.
Fall out of favor with the admin and you lose access to the good American models, aren't allowed to use Chinese ones, and fall prey to the attackers and behind your competitors.
I’m sceptical they could find the legal framework to do this even if they wanted to
They have legal authority to (a) prevent export of US goods/services; (b) ban imports of physical goods; (c) ban transactions (including purchasing services or license agreements) with foreign firms
But I’m not aware of any legal authority which lets them ban US firms from running a Chinese-developed open source AI model in the United States, if they are at arms length from the vendor, and aren’t using it for government contracts or regulated applications
That’s because the Department of Energy originally funded and contributed IP to the EUV Corp joint venture between several semiconductor companies (including ASML and Intel). Their ability to export control EUV was part of that original agreement that the entire technology is built on.
The weights are already available and downloaded, is it going to be a crime to have them, run them, make them available? Constitutional rights still exist (I hope)
> is it going to be a crime to have them, run them, make them available?
Now you're getting it! Commerce will call it a munition and those harboring it as harboring illegal/foreign munitions.
No business will take the hit, so they will quickly deplatform the models.
No end user has the GPU capacity to use GLM 5.2 or similar models at full precision so the government will call the problem "mostly solved." But they might choose to "make examples" out of a few people using p2p software to download the weights if they choose to.
Or we use the models to work on fixing vulns and stop over-blowing the doom scenarios. Gotta save the kids and kill the terrorists though!
I'm for making software better instead of banning it based on what the rich and powerful claim.
I suspect the real fear is that open weight models undermine the financials and token prices they thought were going to pay off their ludicrous spending because they have all raced and raised hardware prices.
We're still in the middle of the cambrian explosion.
If Anthropic was capable of developing Opus 4.49-4.5 2H 2025.... then any company with a research team capable of reading all the papers and press releases will be capable of producing Opus 4.8 by the end of 2027, either raw model competency, or in a harness like claude code (or better with both). I guess what I am trying to say is that Opus 4.5 does not represent the edge of agentic capability, merely somewhere in the thick meaty layer of "functional and achievable".
We can draw the line at Sonnet 4.6 in the US but much like encryption export restrictions in the 1980s, the line drawn will be laughably low within a few years and simply unthinkable in a decade.
I do not think the government thinks this deeply. Market manipulation might be a rational, if unethical reason to ban open source models.
But this admin banned Anthropic models to "own the libs." They will continue to ban what they want for whatever reason they want. I don't think those reasons will be particularly coherent.
Yeah, the current admin is reactionary, they appear to put little thought in, or at least disregard input they dislike. I don't think Ant's ban was about "owning the libs" as much as it was asserting dominance over someone who spoke up counter to the admin's aims and claims. They do listen to money, which is where I see Big Ai paying for executive orders (because the admin forgot what it means to compromise as part of legislating for all americans).
Reaper and Predator are both drones and there’s really no comparison to toy drones in terms of sheer destruction and capabilities in general, the comparison is actually quite apt imo.
> Constant: the IDOR dataset (the same real, open-source applications we've used in prior research) ...
What we're they? Also, wouldn't one expect a more recently released coding agent (with a more recent knowledge cut off) to perform better because they have access to more knowledge about vulns in these OSS projects, and even possibly have knowledge of your own "prior research"?
how representative are Semgrep's benchmarks? everyone seems to have their own benchmark these days (guess it's good "content marketing") I'm honestly losing track
mythos is <10% ahead of gpt 5.5 on all benchmarks, which it gains by being several times the size of opus. had it been economical to provide, it would've been released to the public on day one instead of the marketing circus those effective altruism clowns had exhibited. admitting that it costs >1000% to run inference on a <10% better model would've been very damning.
In my experience, GLM 5.2 is extremely good at finding vulnerabilities, and more importantly, unlike Opus, I've never seen it refuse a command. It genuinely is a very strong model for finding and fixing vulnerabilities.
That's still useful. To paraphrase the kids these days, GLM5.2 is in the room with us, today. Mythos is not. And for us in the EU, it's even more complicated, as Mythos might be with us in the room one day, and go poof the next day, on the whims of political entities that we have 0 control over.
Knowing where open, accessible, local models are is important. We know they're behind. But there comes a time when "good enough" is useful. Even if they're "just IDORs" today, and even if they're behind SotA today.
As someone else said above, GLM5.2 (and other models in the same tier like kimi, dsv4, etc) is / are slowly becoming "good enough" to assist in automated repo prepare work (download, install, test, edit, re-test, etc). And that translates in RL traces ready to be trained into the next generations. That might be more important than x% behind on benchmarks.
Yeah they straight up say that their criteria is narrow and primarily important for their specific use case. Never let rationality cause your pitchfork to be cast away though!
Here, it appears they compare a single prompt "find IDOR", against a multi-agent system. However, one can also start far more sophisticated skills that spin up subagents and mostly do the same in Claude Code, Codex, OpenCode, Pi, etc.
Which I guess makes what semgrep sells obsolete. Unless they have built a pareto-optimal point in terms of capabilities and token usage maybe?
I think the point is less "how can we throw shade on the OP" and more "a harness can enable a lot of models to do very serious cybersec, glm 5.2 is one of them"
Beats which model in Claude? Whenever a "benchmark" doesn't put precise model numbers in their headlines I am immediately skeptical. Either they don't know the difference (bad) or they are benchmarking against weaker models (misleading, also bad).
It's like when studies say "AI is bad at X" and they used GPT-3.5 in current year.
Opus 4.8 according to TFA. Whether or not the safety guardrails were responsible for the difference is an open question but for a dev who wants to secure their software who doesn’t work at one of the blessed Glasswing companies it doesn’t really matter why, it matters what the best tool you actually have is.
This weekend I programmed a matrix bot with encryption and a Rust agent with some tools. Because I need one and OpenClaw just felt... not what I wanted. Two days later and 20 dollars poorer I have what I need: a multimodal agent written in rust that has access to my homelab.
Nothing felt off with GLM. It did what I wanted, was fast, had a decent not very annoying personality and was much cheaper than Opus or GPT.
I used it unquantized through Fireworks, but there are multiple other providers too.
I kind of wanted to see if I can make a Matrix agent from scratch with Rust with GLM and it was surprisingly easy. Just make something for myself how I want it. Maybe I'll take a look on Hermes later...
[1] https://huggingface.co/zai-org/GLM-5.2
Don't worry though, open source evangelists will tell you that these will be running on your phone in the next 3 years.
For $100k you could run this model 24/7 through open router with 10 concurrent sessions at 50tps for a decade and have money left over for a vacation. There's no point in investing this type of money in local models unless you have a business where you're already paying for many employee's individual token usage.
Personally, I’m waiting for hardware to hit the secondary market before I buy something to run unquantized models like GLM. But I have no doubt that I will, at some point.
8 x RTX6000 GPUs cost $100,000 alone. You then need to build a system that can support those GPUs with enough PCIe lanes through a PCIe switch.
It's going to be $120K to $150K to build or buy a system to run this.
The real gangstas are running 16x RTX6000s. Too rich for my blood, and the NV4FP quant doesn't seem to be that much worse.
oil workers buy 100k trucks they do not-much with. why not a 100k in computer?
assuming demand doesn't keep on increasing. even google has trouble having enough capacity apparently.
Claude Code is an agent harness, not an LLM.
Claude is a brand (or group of LLMs), not an LLM.
GLM 5.2 is already capable enough to assist in self-training which is similar to what we saw happen with frontier models and they appear to be getting there at a significantly lower cost than openai/anthropic.
Not that it would make any sense.
Any prohibition on open source models will do nothing to fix the problem.. since attackers will never feel bound to the law. All advanced models must be available for defensive purposes.
If the real motive is profit, then open source models are likely simply not a viable means to that end.
But that's the whole point.
Fall out of favor with the admin and you lose access to the good American models, aren't allowed to use Chinese ones, and fall prey to the attackers and behind your competitors.
They have legal authority to (a) prevent export of US goods/services; (b) ban imports of physical goods; (c) ban transactions (including purchasing services or license agreements) with foreign firms
But I’m not aware of any legal authority which lets them ban US firms from running a Chinese-developed open source AI model in the United States, if they are at arms length from the vendor, and aren’t using it for government contracts or regulated applications
US imposing export restrictions on a model from China?
The weights are already available and downloaded, is it going to be a crime to have them, run them, make them available? Constitutional rights still exist (I hope)
Now you're getting it! Commerce will call it a munition and those harboring it as harboring illegal/foreign munitions.
No business will take the hit, so they will quickly deplatform the models.
No end user has the GPU capacity to use GLM 5.2 or similar models at full precision so the government will call the problem "mostly solved." But they might choose to "make examples" out of a few people using p2p software to download the weights if they choose to.
I'm for making software better instead of banning it based on what the rich and powerful claim.
I suspect the real fear is that open weight models undermine the financials and token prices they thought were going to pay off their ludicrous spending because they have all raced and raised hardware prices.
We're still in the middle of the cambrian explosion.
If Anthropic was capable of developing Opus 4.49-4.5 2H 2025.... then any company with a research team capable of reading all the papers and press releases will be capable of producing Opus 4.8 by the end of 2027, either raw model competency, or in a harness like claude code (or better with both). I guess what I am trying to say is that Opus 4.5 does not represent the edge of agentic capability, merely somewhere in the thick meaty layer of "functional and achievable".
We can draw the line at Sonnet 4.6 in the US but much like encryption export restrictions in the 1980s, the line drawn will be laughably low within a few years and simply unthinkable in a decade.
That would be the rational thing to do.
> financials and token prices
I do not think the government thinks this deeply. Market manipulation might be a rational, if unethical reason to ban open source models.
But this admin banned Anthropic models to "own the libs." They will continue to ban what they want for whatever reason they want. I don't think those reasons will be particularly coherent.
Yeah. Illegal numbers.
Instead of shilling for the LLM providers.
What we're they? Also, wouldn't one expect a more recently released coding agent (with a more recent knowledge cut off) to perform better because they have access to more knowledge about vulns in these OSS projects, and even possibly have knowledge of your own "prior research"?
Secondly these are "just" IDORs, arguably the easiest class of vulnerabilities.
Thirdly it compares to GPT 5.5 and Opus 4.8.
No, we don't have Mythos at home.
mythos is <10% ahead of gpt 5.5 on all benchmarks, which it gains by being several times the size of opus. had it been economical to provide, it would've been released to the public on day one instead of the marketing circus those effective altruism clowns had exhibited. admitting that it costs >1000% to run inference on a <10% better model would've been very damning.
do you have a source for this claim? i thought LLM providers earn high margins from inference (charged by token). is this no longer the case?
> No, we don't have Mythos at home.
That's still useful. To paraphrase the kids these days, GLM5.2 is in the room with us, today. Mythos is not. And for us in the EU, it's even more complicated, as Mythos might be with us in the room one day, and go poof the next day, on the whims of political entities that we have 0 control over.
Knowing where open, accessible, local models are is important. We know they're behind. But there comes a time when "good enough" is useful. Even if they're "just IDORs" today, and even if they're behind SotA today.
As someone else said above, GLM5.2 (and other models in the same tier like kimi, dsv4, etc) is / are slowly becoming "good enough" to assist in automated repo prepare work (download, install, test, edit, re-test, etc). And that translates in RL traces ready to be trained into the next generations. That might be more important than x% behind on benchmarks.
Which I guess makes what semgrep sells obsolete. Unless they have built a pareto-optimal point in terms of capabilities and token usage maybe?
After installing, do a `n8 build` to build the image, then `n8 --danger --provider opencode interactive` to launch it in a container.
Signup for GLM-5.2 here: https://z.ai
I think they give $5 trail credits to test with any of the open weight models.
Beats which model in Claude? Whenever a "benchmark" doesn't put precise model numbers in their headlines I am immediately skeptical. Either they don't know the difference (bad) or they are benchmarking against weaker models (misleading, also bad).
It's like when studies say "AI is bad at X" and they used GPT-3.5 in current year.
How are we supposed to stay skeptical of everything if we read anything!?
This article only talks about detecting vulnerabilities, so it's unclear if it's a true Mythos equivalent.