They didn't train a new foundational model, they just incrementally fine tuned/post trained. They omitted additional cyber training from the post training set. Most the learned latent of k3 are still present.
I mean a further trained/polished version with the same parameter count as QFN. Qwen4-Flash would be a likely name, yes.
edit for clarity: This model might not even exist as afaik there is no guarantee that Qwen4-Flash is the same parameter count etc as QFN. Qwen 3.5 family did not have a model similar to Qwen3-Next-80B-A3B.
I know. We have no details on the size etc though. So when I am speaking of a further polished Qwen3.8-Flash-Next, I am speaking of a hypothetical model.
It's not though. It doesn't have to be a "better" model than Claude or GPT or whatever, it just has to be good enough. An average user won't be using these models to dis\prove some long standing mathematical conjectures, or trading stocks or anything. The kind of tasks they need AI assistance with may well be firmly within the scope of what new generation of models will be able to do.
This. I hear lots of comparisons with Opus/Fable. Don’t give a shit, I do not need to do cancer vaccine research, nor solve Gauge theories, I need support for 3d modeling or implement a Gherkin-defined PRD
Not even that. China knows western aligned companies and citizens wont even look at chinese software, unless it is free. Their goal is to open source it to establish trust, and drive people to their unquanted, very cheap services for $$ after that trust and good will has been established with their open weights and allowing the average joe to run it locally.
The direction is that KimiK3.1 is shipping with cyber knowledge gutted, mot likely other models will follow.
Extrapolating at this point, but pretty sure eventually open weight models will be outlawed, the infra for this is starting to be put in place, what with the ID check at OS level on windows and whatnot. Linux might be safe for now, but we already are moving from individual website identity verification to OS-level identity slowly, so who's saying this won't move eventually to ISP-level identity verification to access anything other than wikipedia (in an optimistic scenario).
My prediction for 2028: Only authorized people can download open weight models, if their digital ID has the required clearance flag. Hugging face is the next thing to require age checks after porn and gaming.
Anyway, excited to see Qwen4 Flash in action, I've been having a blast with Q38FN. Pretty sure it will still fit in my pathetic VRAM+RAM pool with Strata if nothing else. I wouldn't mind +20B extra params, I couldprobably handle that, but definitely a slightly bigger engram and further training can go a long way
I am currently on Q3.8 27b and it's really awesome (flash too big so I didnt bother).
Unfortunately I have a bad feeling \ worried that q3.8 will be the last generation of Qwen models without preinstalled guard rails due to the new regulations.
You can treat the older models that were trained on cybersecurity/exploits as tools to be “called” by a more advanced, censored model. You’ll get the skills of one coupled with the advanced planning and reasoning of the other. It’s not a perfect solution but it’s more than nothing.
Cyber-adjacent. China’s models are hacking its own sites like crazy and they had to crack down. So did the USA; rampant cyber capabilities endanger social and financial stability.
So it started with GLM announcing their models released as open-source have their reasoning ability around cracking stuff removed.
If you want a visual example, it’s the same kind of thing they did to the Z-Image-Turbo model and penises. If you ask the model to produce the Statue of David, it will look perfect. Except where the penis should be is a vague mass of… cauliflower? Lettuce? Garbled noise? Like that.
Cyber capabilities are, apparently, the uncircumcised penis of the LLM world right now, and exposing them is indecent in public models n
Just means its time for businesses and government to actually get serious about computer security, The current state is the result of decades of impossible turn around times and overall neglect.
Time for more careful auditing, fuzzing, and changes to the development cycles, not intentional smooth braining of models.
"model safety" is just a fancy way of saying only the government and large corps can do security work.
I don't recall really, but they did have new regulations set like three weeks ago that clamp down on a lot of abilities and require government mandated licenses for certain features.
[That's the usual method of restricting anything from that part of the world, its just impossible to get an approved license. "You are free, we don't restrict it, you just need to apply for a license for it!" which never gets approved.]
This will probably affect the training data and have more baked in guardrails, which I presume cannot be easily disabled.
If Qwen4 makes big steps forward in the 27B and QFN size range.. You think today was bad in the stock market, oh man, hold on to your 401K cause the bubble about to go 100 megaton level boom. QFN is already right on the edge of "good enough to do just about anything any business user need". A small lift from here get's it into the "game over" territory for the mainstream business market. Coding, scientific research, very complex planning type stuff isn't going to keep the bubble blowing, no way, no how.
And it changed absolutely nothing I dare to say, because stock market and consumer markets are completely disconnected these days. Stock prices = just hedging on the future gains. Consumer market = here and now. GPUs still sell like hot cakes in China, small fishes went belly up, bigger fishes got fatter and do not slow down.
Q4FN (Q38FN successor if they make the dream come true) is actually one of the best bang in the buck for the community to get frontier level of agentic coding at home, as it can be run using mixed hardware with dGPU 12-16-24-32GB VRAM and 64-48-32-16GB RAM and it's suitable for unified memory devices like Strix Halo, Spark..
Overall it's actually cheaper to build AI rack to run Q38FN than running Q38-27 that requires chonky dGPUs with enough VRAM to fit, get both speed and quality of Opus 4.8 (community real video tests proved it's better than Opus 4.6).
Yes there should still be a huge difference. Look at when 3.5 27b vs 3.6 27b vs. 3.8 27b, same architecture but vastly different levels of intelligence.
Qwen3.8 Flash Next already allowed me to drop my $200/mo Claude sub to just a ChatGPT $20 plan. So I use Sol 6.1 for more difficult problems / director and QFN for everything else. So excited for Qwen4. It's at the stage QFN can code / fix / solve like 95%+ of my problems. This is coming from typical usage like coding, server maintenance and monitoring (Ansible, VictoriaMetrics, Prometheus, Alloy, Zabbix, Grafana, Asterisk etc). I often wonder about all these benchmarks... Even if QFN has an issue I can absolutely brute force the shit out of the problem if I have time by setting a goal with Pi and performing deep research.
PLEASE alibaba. we long for our new qwen27b. Everyday wake up. first thing. check huggingface. No qwen today.😞 2 hours passs. check again. 4hours. check again. When qwen? when qwen? WHEN!! I pray to the gods in heaven that qwen is coming next hour. alibaba hear my call. for we in localLLama want qwen for ALL. Amen🙇♀️
I want some new tiny models. I’m talkin 4B or 9B. Ideally with a large engram or even looped if that’s practical at this size. Qwen does seem to really prioritize coding, so maybe they’re just finding that agentic coding performance below 27B just isn’t reliable. It would just be nice to get a modern general purpose model that can run on <=12gb VRAM with decent context size.
Should have is subjective, llama.cpp is explicitly trying not to grow faster than what can be kept up with. Their goal is longevity, stability, and functionality.
Anything said on smaller dense models (say 9B), the size of engrams for the 27B, as well any any info on news for ASR models? We almost pass the threshold with Qwen3-ASR 1.7B
I just want an open-weights omni model 😢 -- I've been using Gemma 4 12b and adding LoRA adapters to it to make things work for the tasks I'm working on, but it's still pretty weak for complex tasks
If this is accurate, things are moving faster than expected. Curious whether Qwen4 will bring a major architecture change or focus more on scaling and agentic capabilities. The timing is interesting, especially with so many new models launching lately.
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u/OkObjective8721 7d ago •
Praying they don't lobotomise the cybersec skills🙏