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  VulgarExigency
  > The first attempt at recovering the key was wrong in a very specific way; it produced a working key and the signature check passed, but a hash the binary computes as an integrity check didn't match. In my experience, most models would have called it done and left it at that, but Qwen 3.8 27B didn't do that. Instead, it highlighted the mismatch, went back to the drawing board, and kept going until the value matched byte for byte.This seems to be a pattern in the more recently released models that I think accounts for an increase in the quality of their work. They are very persistent in verifying that their work is actually correct, so even if they're not as "smart" as bigger models that get it right the first time, they have the ability to follow through to ensure that the work is actually done.
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  djoldman
  > I gave it the hardest real task that fits on one machine: reverse-engineering a commercial app's license check...Respectfully, tasks that allow for explicit straightforward true/false or done/not-done tests are not the "hardest real task[s]." In fact, those are the ones that see the most gains from AI-assisted coding.Testable tasks are where the largest opportunity is.
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  mdp2021
  > As it turns out, probably unsurprisingly, Qwen recognizes common jailbreak attempts, and one of the first things it told me was that it wasn't going to fall for the jailbreak promptNow also see latest submission, https://news.ycombinator.com/item?id=49409073 :# I spent $266 and four AI models to own my tablet. GLM-5.3 finished it in a day> Quick context: the tablet is a 2021 Fire HD 10 that ran my Home Assistant dashboard and kept powering itself off: the logs showed Amazon's own software issuing the shutdowns, and the only permanent fix was root, which has never existed publicly for this model. Anthropic's and OpenAI's cyber safeguards wouldn't touch the projectWhy should Anthropic and OpenAI thrive: they do not work on real problems.
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  exceptione
  Local models would be even better if they did not ship with all the refusal shenanigans built-in. You can safely bet organized crime has access to the best models without these hoops, which makes the case that the average user (=non-criminal) should have access too. As I understood from an ex-Anthropic employee, some orgs got access to Mythos based on their high enough spending level, not on other grounds.Either we are in command over the software, or the corp is in command over us via the software. I can on a theoretical level understand the concerns, but either we ban all LLMs or we have a level playing field for everybody. Let's not forget: defense and offense are different sides of the same coin in software. I guess this wouldn't apply to bio weapons, but I am not in the know about that.
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  pi-victor
  i'm not good with paper work, in fact, i'm horrible with anything that's paperwork related. for the past few days, i ran this model on my rtx 4090 + rtx 3070 and told it to check all the bills, invoices, contracts for me and my small company. i used pi with llama and the pi-llama plugin. oh, boy - i hooked it to my email, told it to download all of the invoices and bills i had for both me and my company and organize them by company/date/ and then merge them with the ones i have locally. it did ocr, wrote scripts, organized everything neatly. i am now the most organized i've ever been in my life. Next: RAG on all the documents and bills i have. if you connect staan-search (there is a pi plugin for that) and ctx7 to this it almost does miracles. the downside is i have to sit next to my noisy threadripper as the magic happens and pay for the electricity, but that's about it, i'll gladly do that. and as i finished this paragraph, it also finished organizing all my personal documents on my san. i don't use the expression "game changer" easily, but it's hard to resist in this case. out of all the models i've used locally qwen3.8:27b blows everything out of the water.my setup# Logical CUDA0 = RTX 4090, logical CUDA1 = RTX 3070 export CUDA_VISIBLE_DEVICES=0,1cd ~/projects/misc/llama.cpp/exec ./build/bin/llama-server -hf ggml-org/Qwen3.8-27B-GGUF:Q4_K_M --mmproj /xx/xx/xx/xx/xx/mmproj-Qwen3.8-27B-Q8_0.gguf --host 0.0.0.0 --port 8080 --jinja --parallel 1 --split-mode layer --tensor-split 6,1 --fit on -fa on -c 98304 -ctk q8_0 -ctv q8_0 --image-min-tokens 1024i load more on the 4090 because it's faster.usually the temp stays around 65 for both. utilization for 4090: 70-90% 3070: 30-50%. I get around 30-40 tk/s. if i offload more to the 4090 the tk/s goes up, but i stress the card too much and that thing now is worth its weight in gold.note: the pi-llama plugin needs a patch for pi to send the model vision capabilities, seems it doesn't work out of the box.
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  saidinesh5
  Lately I genuinely believe that the future will be large frontier models generating and updating inputs/skills for "good enough" local models to solve our daily problems.A lot of tasks which need a bit of intelligence don't really need that much compute. Just good enough documentation / skills, tool calling and a good enough local model.Not sure what exactly this means for all those data centers that are getting built... But exciting times.
• __alexander
  In my benchmark Deepseek-v4-flash did much better than Qwen 3.8 27B at reverse engineering.https://alexander-hanel.github.io/StressingLLMs/
• bluecalm
  As someone who was selling Windows desktop app for 10 years and made nice money out of it I have mixed feelings. On one hand it was always a losing fight against determined hackers on the other the tools weren't widely available so the problem wasn't as widespread. We lost quite a bit to piracy but could still make a decent business. With widely available LLMs I think that business model is truly dead though. Not only hacks/cracks but also any kind of smart idea you may have will quickly be reversed engineered from your binary.If you never lost money to piracy you may think that "those people are not your potential customers anyway". This is not true because people will crack your software and then resell it - often pretending to be legit resellers operating under your brand. To add insult to injury they will send their customers to your support as well.If I ever come out with something smart again there is no way I am shipping it as executable. SaaS it is for better or worse.
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  samuel
  I have this idea of using an obliterated version of this model for cyber work(or even this one, seeing that its guardrails aren't that strong) in a harness with the ability to spawn SOTA level subagents, faster and more capable.The rationale is that the manager model sees the big picture and knows that the task is "unethical" while sota models are just given very isolated technical tasks that don't trigger any refusals.Has anyone tried this? I would love to know about previous attempts of this approach.
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  jnwatson
  I can't get Qwen 3.8 27B to do a simple code review on a fairly basic Python file. With thinking on it just ruminates forever and with thinking off it gives obviously bad borderline hallucinating advice.Edit: I tried again with the 2.4T model and it still ruminates to death, but with thinking turned off, it generated genuinely useful advice.Edit2: adding --reasoning-budget 8000 --reasoning-budget-message "Reasoning budget exhausted; give the final answer now." --reasoning-effort low" to the llama.cpp executable parameters produces pretty good output.
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  topper00_raptor
  Why does the screenshot on your pi terminal shows opus-4.6-medium from your claude subscription ? Instead of Qwen ?
• geye1234
  I'm far from being an engineer, but I can code a bit and have an engineering-adjacent role, and 3.8 27B "seems" -- purely subjectively -- miles ahead of 3.6 for the medium-difficulty tasks I give it. In particular, it's only started looping once in the 2 weeks or so I've had it. 3.6 did so every day.I normally run with thinking low but it's still miles ahead.I had been annoyed at not being able to run 0731 locally, but now I'm not sure I need it. I think I could leave 3.8 running overnight without waking up to find my office sweltering at 80F and seeing eternal loops on my screen.
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  jchw
  I'd personally like to know more about what tools it used/wanted and the harness setup, because this sounds pretty cool. I have a dual Arc Pro B70 setup and currently get around 22 t/s which isn't great but isn't terrible either (it is at least less quantized.)I've seen GPT 5.6 Sol happily invoke objdump and even write jobs to run headlessly which Ghidra when trying to disassemble a binary.
• anon
  undefined
• ianmarcinkowski
  I used it with opencode to build an admin UI for a React slideshow presentation app I use to do presentations. It worked pretty well on a 64GB Mac M3 Pro and took 1-2 hours.
• throwa356262
  Thanks, now I too want a Lenovo Thinkstation PGX...I think it will be fairly easy to remove refusals from open models. Feels like a lost battle, so why does Alibaba even bother?
• EGreg
  Can you give it a task like “Prove or disprove the Riemann hypotesis, keep going until you’ve done it” and see how long it takes? :-)
• freepiai
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• shahariaa
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• luciana1u
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• sm_ts
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  RobertasTa
  [flagged]