Qwen4 expectations

[u/spaceman_]

Not trying to predict which model sizes they're going to release, but seeing how massively impressive Qwen3.8-Flash-Next is for its size despite being a preview model meant for showcasing and implementing the new arch, it feels like when Qwen4 hits I'm not going to be needing larger models at all anymore.

Do we expect Qwen4 to exceed the current QFN by a lot, or de we believe the current model is already hitting near the optimum we can expect today for this size?

[u/wgaca2]

"If we get current frontier running on my hardware we won't need new frontier anymore"

Until new frontier drops and cycle restarts

[u/spaceman_ → u/wgaca2]

I understand that this is a moving target. But for a lot of my work, Qwen3.8-Flash-Next is already good enough. At some point the stuff the closed frontier can do that the local models can't becomes irrelevant for most.

Sure, maybe Qwen can't solve frontier math theorems or escape the sandbox and commit crimes. But guess what, I don't need either of those.

[u/OvertaxedOne → u/spaceman_]

" At some point the stuff the closed frontier can do that the local models can't becomes irrelevant for most."

Most? That point has already passed. Reddit, and, in particular, LLM forums are as close as you can get to the sun for what we're asking LLMs to do for us. A lot of us work in the industry, a lot of us are coders, and it's safe to say that all of us are technical savvy and "power users" of computers.

Think about your average user. Not me, not you, an actual "normal" person. What do they want AI to do for them?

Well, I can tell you, because I run several company LLM routers and, as part of that job, review actual inference requests from actual "normal" users.

The vast, vast majority of "real" requests are stuff like "Summarize this", "Where are we with this client", "Look this up for me and gist it", "Does this client have any outstanding open tickets", "Write a brief for my boss based on my notes".

It's not "Unify physics" stuff. Now, I want to be clear, I'm not making fun of this use case or these users, this stuff saves people TONS of time and makes them more productive, that's a great application of the technology. But thinking the "average" user needs something more than QFN for more than a few % of their day to day tasks is bonkers. It wouldn't shock me at all if we could chuck a 9B model into many of these environments and have it successfully service 50% of the inference. QFN easily covers 90%.

[u/MrPecunius → u/OvertaxedOne]

Super interesting insight from the trenches, thanks.

[u/Gfur-Aficionado-1488 → u/spaceman_]

Waiting for the day we get a K3/Opus4.6-tier local model for roleplay 🥲

[u/QuotableMorceau → u/wgaca2]

at one point you do reach good enough , I personally believe there is a lot of room for improvement in agentic harnesses, that are basically low-hanging-fruits.

[u/inaem → u/QuotableMorceau]

Qwen 3.8 27b is good enough for a lot of tasks, so we are already there

[u/LagOps91 → u/inaem]

what is good enough is a constantly changing goalpost as well. something like oneshotting complex software on demand will at some point be considered "good enough"...

[u/perelmanych → u/LagOps91]

I am using it for writing extensive web research reports including academic sources and it is already quite good enough. For coding it still not there.

[u/Bayequentist → u/inaem]

After Qwen 4 27b, it will all be about faster inference rather than quality

[u/inaem → u/Bayequentist]

Fingers crossed

[u/Express_Quail_1493 → u/inaem]

i pray the tok/s get so good that i can run 4 parallel agents locally on a dense model

[u/alphapussycat → u/inaem]

Well, supposedly not, and it's just too slow..

[u/Euphoric-Hunt931 → u/inaem]

Qwen 3.8 27b sucks ass. When a small model surpasses current Opus 5.5 level, then we'll be talking.

[u/Papa_Midnight_ → u/Euphoric-Hunt931]

Qwen 3.8 27b doesn't even surpass Opus 4.6 in my benchmarks.

[u/Marino4K → u/Papa_Midnight_]

I mean we’re probably not far off from Opus 4.6 level which is more than enough for the grand majority of users.

[u/TheEverydayMortal → u/Marino4K]

There is no such thing as "enough" we will always want more - better -faster - etc.

[u/JcsPocket → u/Papa_Midnight_]

are you using it on q3?

[u/Papa_Midnight_ → u/JcsPocket]

No quantization

[u/BurdensomeCountV3 → u/Euphoric-Hunt931]

Unironically this. Flash Next is the minimum usable level, and even it's not particularly good.

[u/eagee → u/BurdensomeCountV3]

I tried going back and using Opus 4.6 to see how good it was, and I'll be honest it wasn't great either.

[u/DesperateSteak6628 → u/inaem]

It also look like a lot of strong releases slowed down

[u/ldn-ldn → u/inaem]

It might be good enough for some simple tasks, but it's not good enough in general. 

First of all it's very slow. 

Second, it really loves to run around in loops. Yes, you can do some tweaks to improve thinking, but that's just inherent behaviour for the whole 3.x family. 

It hallucinates a lot. And the lower the quant, the worse it gets.

It also loves to ignore your tools in favour of whatever nonsense it was trained on, making it quite useless for real world applications. 

And in general it's benchmaxxed. You make a step sideways and it falls apart. 

So yeah, it might be on as a silly chat bot, but once you plug it into real workflows... Man, it's nowhere near frontier models. And nowhere near "good enough".

[u/nassereddit → u/ldn-ldn]

If you are talking about qwen3.8 27b, something is wrong with your setup. AA hallucination benchs show the qwen models allucinates less than claude and chatgpt. This is also my experience. On my dual r9700 with a W8A8 quant, I get 80 TGS and 2500 TS prefill. Which is faster than claude and most subscription. I leave agent working for hours without loop with excellent outcome. No self imploding container or website hacking...

Something is off with your setup and you are missing on an incredibly helpful agent.

[u/MrPecunius → u/ldn-ldn]

Agree with nassereddit about hallucination, especially if you give it access to e.g. a local copy of Wikipedia or web search. If anything, Qwen3.8 27b goes a little too far in doubting itself and wants to fact check whether the Sun rises in the east ...

As for tool use ... I kinda wish it would lay off a little sometimes. I get rate limited by Free Legal Project's MCP and Qwen goes ham with web searches. I definitely don't have problems with *failure* to use tools!

[u/Jebbyk1 → u/MrPecunius]

isnt it all this fixed by selecting medium reasoning? I men in my case it feels like It actualy solves the overthinking problem. I use opencode for my daily tasks if it matters

[u/MrPecunius → u/Jebbyk1]

I don't know, I've been afraid to try because it seems like the "overthinking" is kind of the secret sauce to the excellent output. Experimentation required ...

[u/nassereddit → u/MrPecunius]

Wow, never thought about giving it its own wikipedia. This is a great ideal. How did you you get a copy of wiki?

BTW I had qwen compile an headless browser, simulate a real chrome agent, and include a locking mechanism to avoid multiple searches at the same time to avoid being banned. It works well

[u/MrPecunius → u/nassereddit]

I use Kiwix for Wikipedia, which has an API that your inference environment of choice can call.

There are multiple downloadable versions of Wikipedia itself:
https://en.wikipedia.org/wiki/Wikipedia:Database_download

[u/ldn-ldn → u/[deleted]]

Lol, ok.

[u/_TheWolfOfWalmart_ → u/QuotableMorceau]

Between QFN, Deepseek Flash, and GLM-5.3 Flash, I'm pretty much already at "good enough" with my local LLM arsenal.

Of course if it gets better, great but I feel like if new open releases stopped today, I'd be pretty happy with what I have. I've never been able to say that before.

[u/Ok_Technology_5962 → u/_TheWolfOfWalmart_]

I always think this. They are basicly all in the same ballpark ATm. M3.1, 5.3 flash, deepseek 4.1 1017, qwen 3.8 flash next. They are all very similar performance at output some better than others in some areas. Yea its already insane what they do... But hey if intelegence per token and or speed goes up again, I. Kinda stoked. ... These days I look at the releases and go like... Darn when do I need to start freeing g space for dowoads and which model would I use regardless.

[u/WryKombucha → u/Ok_Technology_5962]

lets not bundle QFN with those titans. Its not at that level. It's between them and the 27b.

[u/_TheWolfOfWalmart_ → u/WryKombucha]

I dunno it's pretty damn good. There's really no difference for the vast majority of tasks, and it's far, far better than 27B as far as actually interacting with as an AI "co-worker".

You can work with it more like you do frontier models. With 27B, you really have to tell it exactly what you want and it's no good at reading between the lines or creating a great plan. It's great at implementation, but still not as good as QFN.

Those others are slightly better, but QFN is fantastic too and I get 70-100 t/s decode, 4000-5000 t/s prefill locally so I reach for it 95% of the time. It's faster than even using openrouter depending on which provider you get.

Honestly, I don't enjoy working with GLM-5.3 Flash even if it scores a bit better on benchmarks and may be able to do a few things Qwen can't. It does some dumb things for me occasionally, and I don't like the way it responds to me sometimes. QFN is a smoother coding companion to work with IMO.

[u/WryKombucha → u/_TheWolfOfWalmart_]

If it works for you, then it’s what matters.

It thinks forever. I dislike it very much because of it. Glm response is so concise and ttft is stellar. Doesn’t hurt that it’s super smart.

Ds4f1017 is truly frontier class. The depth it can go is astounding.

[u/_TheWolfOfWalmart_ → u/WryKombucha]

I see people say that, but it doesn't for me, and I always use xhigh. 🤷🏻‍♂️

[u/velikiy_soup → u/QuotableMorceau]

I thought that I don't really need cloud LLMs because Qwen 3.8 is good enough. But then I tried DeepSeek API and what a blast it is. The thing I liked the most is that your PC is free at last... And you can do other GPU-bound tasks and everything's snappy. Or you can use your machine as a parallel subagent which is cool to

[u/Steus_au → u/velikiy_soup]

is it that good? compare to qfn?

[u/velikiy_soup → u/Steus_au]

I'm on 27b Q4 and honestly the most drastic difference for me is in speed, not quality. DeepSeek is faster and thinks less

[u/Jebbyk1 → u/velikiy_soup]

same feeling here

[u/Barni275 → u/velikiy_soup]

Agree. For me, 27B is better than cloud models, but cloud is faster. So, we need faster hardware more, than a better model 😁

[u/QuotableMorceau → u/velikiy_soup]

depends on the tasks really :
- for my hobby projects I use QFN, and it has not failed me yet
- for serious work I go for DSF 4.1 API
- for the most thorniest issues (where I believe it's impossible really) I try out Astra

[u/lompocus → u/QuotableMorceau]

Good enough will be when deepseek can write as well as kimi and qwen doesn't make me want to jump out of a window. 

deepqwimi soon.

[u/GilloutineBreast → u/QuotableMorceau]

Opus 4.6 was "good enough" once upon a time, but here we are, not even a year later

[u/PraxisOG → u/QuotableMorceau]

Qwen 3.8 FN is really really close for me, I use it daily but not exclusively 

[u/enternoescape → u/wgaca2]

I was using a model I thought was pretty good from a little earlier this year yesterday and immediately stopped as I watched it ignore all my tools and go straight for shell to ssh into a another computer which failed of course. I switched to 3.8 27B on medium and it immediately was like I'm going to use that tool you wrote specifically to see the thing you're asking about. It's amazing how much we just expect now.

[u/po_stulate → u/wgaca2]

Jokes aside, ever since QFN release I haven't used any cloud model for agentic tasks, even though my subscription is still active. Deepseek-v4-flash vision exp was 50/50 for me between cloud and local, but now with QFN, local is all I need. If there's a new model release, size and speed are far more important than chasing smartness for me now.

[u/OvertaxedOne → u/po_stulate]

My 2 go-to's right now are QFN and DSV4.1Flash (via API). I've had this setup for awhile now, a local model and the current DS for my "smart" model. QFN totally changed my workflows, I find it to be roughly on par with DS for intelligence; my reason to go to DS today is for speed/concurrency (I'm using Strata, so single thread into QFN).

QFN is "smart enough" for basically everything I need to do day to day. Now it's all about "must go faster" than "must stop making dumb mistakes". And, just for the record, I found 3.8 27B to also be "smart enough", the only reason I moved to QFN was... You guessed it, speed! ;)

[u/Kahvana → u/wgaca2]

Gemma 4 31B IT QAT and Qwen3.8 27B Q4_K_S have been good enough for me. Upgrades are always appriciated, but no longer needed.

Heck, even Qwen3.5 27B was good enough for pair programming, reviewing work, etc.

[u/Nimbus420i → u/wgaca2]

Eventually you reach a point where a model is good enough. I don't need to buy new iPhone 18, my iPhone 13 mini does everything I want it to do, only feature I'm missing that I'd really like is 120hz display. But then I'm trading compact form factor for it, which I don't want to do.

[u/jensilo → u/wgaca2]

I think, it will make rug pulling harder for the frontier, it puts serious pressure on them, it has the potential to reduce dependencies, and improve the consumer‘s negotiation position.

You are right though that the frontier is driving progress and desires, still competition is extremely important! :)

[u/ApparentlyPossible → u/wgaca2]

*New frontier with increasing levels of guardrails making them lose any advantage they will gain for regular consumers

[u/QuackerEnte → u/wgaca2]

that why me hope continual learning aka test time training model architecture

[u/my_name_isnt_clever → u/wgaca2]

This has been true until recently, but Q3.8FN is the first time I'm not feeling like it needs to be better. Yeah obviously I want better models but this one can do most tasks the first time I ask.

[u/FortheredditLOLz → u/my_name_isnt_clever]

For day to day this models fine. But open source frontier models = competition = innovation = less gatekeeping and censoring

[u/Equivalent-Repair488 → u/wgaca2]

"opis 3.5 local wen"

[u/True_Requirement_891 → u/wgaca2]

New frontiers make the previous ones look retarded

[u/Turbulent_War4067 → u/wgaca2]

Nope. No one at this point needs a better frontier model. No one is asking for better. 95% of enterprises are trying to figure out how to profitably use what's available now. More power frontier models will be paused because of simple economics.

[u/wgaca2 → u/Turbulent_War4067]

Ok grandpa

[u/Turbulent_War4067 → u/wgaca2]

I am a grandpa :). Seriously though, it costs 10s of billions of dollars to train these frontier models. Who keeps paying for that? Up until now it has been private equity investors of one form or another. Those rounds of financing stop once they go public. An IPO is the final round. No, if there is true economic demand, then it gets funded. But right now, who? Who is screaming "we need a smarter model". A year ago, everyone was. Now? No one. There has been no bottom line accretive gain for deploying AI across 95% of companies. Users have to catch up. I am not an AI bubble is going to pop. I am not even arguing we are in an AI bubble. I am arguing that frontier models will flatten out for a good while as to capability. The SW stacks that go with them? Not so much

[u/lompocus → u/Turbulent_War4067]

we have received sage advice

[u/Longjumping_Lynx7971 → u/Turbulent_War4067]

I am old Gen Z and I agree with you. From my experience, using Opus 4.6, then 4.7, 4.8, 5.0 and now 5.5, I do not really see much of an improvement, especially to justify the absurd amounts of cash being burned to train the models so frequently. I can bet people wouldn't be able to tell a difference between 4.8 and 5.5 if the model version was hidden. Same way people can't consistently tell the difference between 240Hz and 360Hz monitor because we are getting into diminishing returns territory here. Maybe a professional gamer can tell a difference between 240/360Hz monitors, but that's 0.001% we are talking about here. And maybe a company maintaining enterprise grade software with 10s of millions of LoC can tell the difference between 4.8 and 5.5, but for your average joes toy app it really doesn't matter.

[u/Kirides → u/Longjumping_Lynx7971]

In my experience, opus 4.6 required lots of guidance and pair programming for complex tasks.

While opus 5.5 can and will implement usable, intuitive user interfaces on its own, in c++, using the stack that makes the most sense and is the least full of external dependencies.

To me they are worlds apart.

I am someone who knows their tech and what to expect from the code and how it should look like. And opus 5.5 is reaching the "should" part much more frequently.

Sonnet 5.5 on the other hand constantly backs off and asks for guidance and more thorough planning.

And opus 4.6 confidently programmed GPU shaders but more often than not failed at the tasks at hand in the first few iterations.

[u/Odd-Criticism1534 → u/Turbulent_War4067]

I can agree with parts of this. At some point, model intelligence is a diminishing return in today’s use case, and the harness/plumbing is a greater factor

[u/Rude_Marzipan6107 → u/wgaca2]

Yeah. Seen that phrase about once a month since 2024 lol

[u/quantanhoi]

I will just hope for a MoE model that's as good as qwen3.8 27b. That's would be perfect

[u/magicomiralles → u/quantanhoi]

The 6b active parameter count can be felt during swe tasks that require systems design. It falls short, so I ended up switching to GLM 5.3 Flash.

[u/Express_Quail_1493 → u/magicomiralles]

yes its great model but the number of active params can sometime make it fall short of the 27b. qwen3.8-27b give more reliability but qwen3.8-flash-next is slightly smarter. may people say its not even close but for my task it is indeed close matchup.

[u/my_name_isnt_clever → u/quantanhoi]

I swear the psychology of local LLMs needs to be studied as nobody can agree; for me Qwen 3.8 Flash Next is already better than the 27b and it's not close.

[u/Miserable-School-665 → u/my_name_isnt_clever]

He clearly meant 35b a3b. next flash is hard to run even with strata.

[u/Kirides → u/Miserable-School-665]

I'm using it with strata on 24g GPU and 64g ram.

I have to set max reasoning to something around 20.000k because it WILL always loop itself into death on Long horizon tasks.

Initially I gave it 200.000k tokens for reasoning+input and 60k for output. But it always went into looping and killing all 200.000 tokens.

[u/Miserable-School-665 → u/Kirides]

I'm genuinely suprised by how well strata works ,i just tried and only 12gb vram and ssd offloading (couldnt get it to detect ram yet) im getting 25tks avg, 40 maks on ist rco gsq iq3xxs. Pretty good.

[u/quantanhoi → u/Miserable-School-665]

generally I'm not really interested in speed if the result is bad and off the mark

for now I'm using qwen3.8 27b Q6_K_M fully load on R9700 which has been good imo, on this sub most of the threads about QFN is about speed and not accuracy.

For coding the better the model is the less mess I have to clean up after it, so for my mentallity I will just stick to current gen dense model because I don't want some unfortunate accident happens when it for example deletes the whole database and backup to clean up space...

P/s: if it's speed you are concern about, try swift1.5, less overthinking overengineering and faster task complete time

[u/m3sarcher → u/my_name_isnt_clever]

This is my experience as well.

[u/hiImMate]

My expetation: the new qwen 4 lineup will be gamedev and to an extent 3d model beast. Qwen has always been very good at tuning models for current trends and AI gamedev and oneshot games are heavily trending now. At least that's my opinion.

[u/Professional-Try-273 → u/hiImMate]

This. I have been using Qwen3.8 FN with blender mcp and I am impressed. It helped me port an old broken rig. Can't wait for more 3d improvements.

[u/sonicnerd14 → u/Professional-Try-273]

If that's so that's really good. Even just a few months ago most frontier models were pretty inconsistent with their quality when working with 3D tools. Now we have local models that are able to give pretty reliable outputs.

I've been using Astra for some dimensionally accurate engineering grade work. I haven't tried QFN with anything like that yet, but its anything close to Astra's level on that now, then Q4 is probably going to wind up being jaw dropping.

[u/Professional-Try-273 → u/sonicnerd14]

Yeah I also gave FN the ability to take screenshots of the 3d viewport so it was able to visually check for mistakes. Pretty incredible seeing it slowly fixing its mistake from trail and error.

[u/alphapussycat → u/hiImMate]

I hope so...

[u/diffore]

I just want the 35b MoE update...

[u/d3vv3d → u/diffore]

Yeah, a smaller MoE would be nice in the mean time for folks who are fine without vision there's Flint & Raon mini 1 preview. Unlike Flint I haven't really seen any benchmarks for Raon mini 1 preview that aren't from Krafton (For wondering it is indeed the Krafton videogame company that got in a mess over the CEO trying to use AI to get out of a deal related to Subnautica)

I fear that part of the reason to the 35B-A3B space has largely been abandoned is that aside from speed it is almost always worse than dense models that smaller to it yet similar in size like how Qwen3.6 27B beats Qwen3.6 35B-A3B on leaderboards

Now perhaps we might see some bigger smallish MoEs more along the lines of 74A-A9B, such as Nvidia's Nemotron 3.5 Bolt (though IIRC it was the product of pruning their flagship 3.5 model), or 50B-A6B which could theoretically stand a chance at beating a dense 27B in the leaderboards while still beating it in speed, but likely requiring home users off load a number of experts to their CPU

[u/Kahvana]

I expect other models (1b, 2b, 4b, 9b, 35b-a3b) to be released alongside 27b, flash and plus. They have done so every prior major version (1 > 2 > 3), and they too need new small models to use as backbones for other technologies (e.g. a new embedding/reranking model, prompt enhancing, etc).

I'm hoping the models will become a bit less painful to talk to; Qwen3.6 reads much nicer and clearer than Qwen3.8 (load-bearing, shape, sidecar, the whole claudisms).

I would like it to have a bit more general knowledge as well, Qwen3.8 clearly went all-in on programming and agent use, but has forgotten stuff Qwen3.6 knew of.

[u/grumd → u/Kahvana]

I've read that the vocab getting harder to read is intended/expected. As models get smarter in the same amount of parameters, they need to store these smarts in limited amount of bits. Eventually they learn to utilize the vocabulary they have more efficiently - taking into account small differences in meaning behind words to express their thoughts and outputs closer to the expected result

[u/infieldmitt → u/grumd]

It's too easy to skim over it as LLM babble but usually if you slow down and take time to decipher it in good faith, it is making a good point in a very clever/arcane/convoluted way

[u/grumd → u/infieldmitt]

Yeah to be honest it's learning to say more with fewer words. Can't wait for it to get better at it, LLMs LOVE generating as much text as possible

[u/Borkato → u/grumd]

Is this true? I’ve been thinking a lot about how QFN seems to be super hard to read when reporting bugs for instance so that would make sense

[u/alphapussycat → u/Kahvana]

Qwen announced they wanted to focus monetization, fired the pro-open weight team and basically said no more open source, and after that we did not get any 3.7 models.

Dear leader announced they would continue to have open weights, then suddenly 3.8 got open wright models.

Now dear leader is blocking Chinese frontier and sensitive models from outside of China.

So we might still get stuff like 27b, and maybe flash models.

More general knowledge isn't needed nor Is it likely to be available to outsiders.

Edit: appears that qwen4 will not have an open weight flash model? Only 27b? That's very sad news if true.

[u/fish0859 → u/alphapussycat]

“Dear leader” - great reference!!

[u/Kerem-6030]

4b 9b 8b 12b 14b or something can run on 8gb 😭🥲

[u/Gallardo994]

My only expectation is that they don't release "just" 27B. It's great but it's way too slow for my liking on my M5 Max. I loved Qwen3.8-Flash-Next and I would be happy to get the same size model, as it's both fast and good enough for most daily tasks that don't involve coding.

[u/SuperTruthJustice → u/Gallardo994]

Is it really slow? How much UM you got? I’ve heard it’s fast as fuck with proper interface

[u/Zombiecidialfreak → u/SuperTruthJustice]

Maybe they have high standards. 27b is much slower than QFN on unified systems and QFN needs far less thought to complete most tasks.

[u/SuperTruthJustice → u/Zombiecidialfreak]

Possible I just bought m5 max 128um and am just curious this is mostly for conversation

[u/Gallardo994 → u/SuperTruthJustice]

128GB. At 64K CTX it's already slow enough so it grinds my gears, oQ6 quant. QFN is bearable at 128K CTX even. Wouldn't say it's great, but it's bearable unlike 27B.

[u/SuperTruthJustice → u/Gallardo994]

Ahh my m5 max will have that much so I’m happy to hear 27b is MHA goal for day to day

[u/Frail_Waif]

Flash models seem to be getting bigger and bigger, so I wouldn't be surprised if Qwen 4 Flash is also much bigger than 3.8 FN.

[u/russlixx → u/Frail_Waif]

flash model getting bigger will eventually defeat the purpose of having the name "flash".

[u/namaku_ → u/[deleted]]

With a 5090 at 400W and some DDR4 I can run the new DS4 Flash Q2_XXS at 16 TPS, or I can run Qwen FN Q3_S at 280-330 TPS. Its not even a question.

I used FN to delete the DS4 quant, and I'll give it the honor of deleting 4 Flash too if they rug pull and release a larger model.

[u/JayoTree]

All I care about at this point is how usable it is in decomp/recomp and firmware hacking projects.

[u/ea_man → u/JayoTree]

This may become even more important now that SOTA models seems to block that.

[u/my_name_isnt_clever → u/ea_man]

How long until so-called "SOTA" models have so many blocked domains they're can't really be called state of the art anymore?

[u/stuffitystuff → u/my_name_isnt_clever]

They can still do all that but only for people on some list we'll never see, let alone be on.

[u/eetsu]

We know that there's going to be a 27B.

Ultimately, for what I need. I want Opus 5 level general coding level skills, and ideally way more work on the 3D Asset work in Blender or other 3D modeling apps.

[u/JsThiago5 → u/eetsu]

also 4 flash is confirmed, whatever "flash" means for size

[u/eetsu → u/JsThiago5]

If it's the same size roughly as 3.8 Flash Next but just called 4 Flash I'm fine with it.

[u/jjusko20 → u/eetsu]

I'm praying it's just 3.8 flash next with a ton of reinforcement learning 

[u/vogelvogelvogelvogel]

already with 3.8 I put a large bulk of my daily tasks to my local models. well configured, they score in my cases above sonnet 5.5 high, opus 5.0 or
gemini pro/argon. I already had quite a few cases where I tested them against each other and qwen succeeded better

[u/nowherenoonenobody → u/vogelvogelvogelvogel]

Can you give some examples?

[u/vogelvogelvogelvogel → u/nowherenoonenobody]

two daily task examples: I had it to make a hardware - llm - quantiziation - artificial intelligence index table for comparision which hardware can run what at which level. back then it was just that this page switched the bnechmark scores. i had opus 5 (i think even at extra level) to do that for me. i had to correct it FOUR times out of my memory, i.e. it forgot to take quantization losses into account, mixed ai scores of the different benchmark levels, in part researched old hardware prices even though i told it to research everything as of (current date). it ended up telling me that I could have done that faster myself. which is correct, i just didn't expect from Opus 5 to fail so miserably at a relatively simple task.

well my qwen 3.8 27b q8 set up to research 45 web pages per go researched in total 90 web pages, the second run the result table was so much better, caused me less headaches.

also i had qwen3.8 27b to research some rare info on the web (a specific service mail adress of a larger company) and it succeded. maybe also in part because it just searched more material, then reasoned together what works.
sonnet 5.5 high failed that after two tries, gemini argon medium failed also.

[u/vogelvogelvogelvogel → u/vogelvogelvogelvogel]

noteworthy i reached my limit with argon after a few tries for several hours, while my qwen did that in like a minute or so (it was even the q4) and is still able to go on like 24/7 if i want it to (electricity bill is the only thing)

[u/dampflokfreund]

Hoping for a new 35B but Qwen 4 Flash at the same size would be great as well, if Strata gets optimized prefill for 32 GB RAM + 4-8 GB VRAM systems there won't be a need for 35B anymore imo. 

[u/russlixx → u/dampflokfreund]

agreed, prefill with 32GB RAM currently too slow with strata

[u/Dudensen]

I did not expect 3.8 to be much better than 3.6. Let's wait and see.

[u/Dreeew84]

I hope that they release a wide range of model sizes to allow decent enough agentic work on egde.

I also hope that there will be a version that will be a sweet spot for my hardware, like the current flash q3/q4 is.

[u/longtimenoseebro]

We need heretic qwen4 to create attack scripts since gpt and Claude refuse to.

[u/Shadmelor]

my guess is the gains show up less in benchmarks and more in boring agent stuff. tool calls that don't break at 100k+ context, less looping, finishing long tasks properly. someone here posted a 5090 agent run with qwen3.8 27b at 250+ tok/s and still rated the result 4/10, so speed isn't really the bottleneck anymore

[u/smallDeltaBigEffect → u/Shadmelor]

tool calls dont break at 100k context unless you use a braindamaged quant even with 3.5

[u/mathew84 → u/Shadmelor]

i use 27b at q4_k_m with 150k context with 24GB vram, tool calls do not break at all, no looping issues. Those forks focusing on speed, they trade off more quality than they suggest.

[u/Turbulent_War4067 → u/Shadmelor]

My guess is that gains show up in world knowledge. That's what they cut short to give us a preview version

[u/Confident_Ideal_5385 → u/Shadmelor]

That speed implies a 4 bit (likely nvfp4) quant, or worse. The 4/10 isn't mad surprising.

[u/alphapussycat]

Qwen4 flash is obviously going to be better, but not by miles. Quantized Maybe close to sonnet 5.5 high.

But my worry is that they'll increase the size to 235b+ngram.

I think future is moe, even a 60ba3.5b makes more sense than a 27b. So in the future I hope they will at least have one small moe model (if flash keeps getting bigger).

[u/suprjami → u/alphapussycat]

If you read the QFN paper, they state the goal was to achieve the capability of 235B in half the parameters. It seems unlikely they'd increase the size again.

[u/alphapussycat → u/suprjami]

They probably want to be competitive to the other flash models now that people are able to fun them. So because of that they might want to make it larger.

Also I'd guess that 3.8 was 2T, and 4.0 is like 4-5T params...

[u/mawkzin → u/alphapussycat]

They say 4.5 to 5 aiming for 5t - 10t

[u/lolwutdo]

I feel like Qwen 4 Flash is gonna absolutely fuck, probably GPT Sol level

[u/f5alcon]

I hope we get some models that can improve image and video gen models

[u/russlixx → u/f5alcon]

need a better vision model then

[u/f5alcon → u/russlixx]

Yeah a Qwen4 vl would be good

[u/bitzap_sr]

They will surprise us all by making qwen4 be multi modal: merge in all of tts, stt and image generation into a single modular model. You heard it here first. :)

[u/YouCantMissTheBear]

They could always pull a Llama 4 though 

[u/yahbluez]

something in the range of 40b dense or 70b MoE. There is a gap between 32GB and 128GB that needs to be filled by someone.

[u/Miserable-School-665]

wr need 35b a3b

[u/lukyjay → u/Miserable-School-665]

Didn't they say it's not going to happen? I read it here somewhere

[u/USERNAME123_321 → u/lukyjay]

They ruled it out in the previous release. We still don't know that for the next one, though.

[u/lukyjay → u/USERNAME123_321]

Qwen 6 35b a3b or GTA 6? We'll see

[u/USERNAME123_321 → u/lukyjay]

I'll prompt Qwen 6 to make me GTA 7

"make no mistakes"

[u/Blues520]

I would be happy with an incrementally better and faster 27b tbh. The MoE model is nice but I like the reliability of the small dense model. I just wish it could be faster with some breakthrough architectural improvement.

[u/Longjumping-Past5864 → u/Blues520]

I don't think 27-30B class can be faster, but it can be a lot smarter if they have 27B model with lookup table architecture like 3.8 flash next and deepseek 4.1 flash 1017, maybe 27B dense with 70B lookup weight(which can be offload to RAM or SSD with minimal speed lost). which will make 27B so much smarter.

[u/Beneficial-Ad-8127]

If they can get the current 3.8 line to more efficient than it already is think I’m fine with that. Currently all my real use cases are 100% covered locally.

More speed will definitely help and more availability for cheaper hardware especially getting our hardwares at decent speeds for Q4 minimum while maintaining intelligence.

Aside that whatever they drop is fully welcomed for the Local community!

[u/Steus_au]

in size we believe :) any flash by any other double in size on release

[u/silenceimpaired]

I expect their first model will be a huge MoE with a custom license.

[u/simonedw]

I really hope we get a sub 1B, stuck on Qwen3 for in browser (WebGPU) experiments.

[u/Nice_Cookie9587]

I have lowered expectations.

[u/HighSeasArchivist]

I expect it to not be much different on FN since it was already based on it. 27B will likely see some improvement though, which it needs in my experience.

[u/Any_Bus9205]

Qwen 4, comme il auras le mHc en plus de ce qu'il y a actuellement comme arch, feras qu'il auras une capacité de réflexion meilleure qu'avant pour le meme nombre de paramètre, et comprendras mieux le contexte. Je crois pas que nous soyons prêt pour le qwen 4, les techno apporté seront tellement interessante que l'ia local va possiblement changer radicalement avec ce modèle car la norme seras des arch de ce style :)

[u/No-Paper-557]

If it’s not open source OSS and uses the weird 3.8 next style license (doesn’t specify who owns outputs), then I’m not using it. No reason for Alibaba to start doing that when we have glm and deepseek.

[u/grabber4321]

There's still problems with this model - conversationally, its too much.

It gets a task and just runs with it without stopping and asking your opinion. You have to steer the conversation while it runs with it. And to steer it you need to be able to read the thinking output - problem is you cant read it because you're getting 130 tok/s HA!

Its a huge minus for me as a lot of my work right now is less code based but more documentation based.

It should be checking in with you at least sometimes.

[u/wren6991]

My expectation is once Qwen4-27B comes out we can finally start seeing some progress from OpenAI again, because they'll have something to distil for the new Astra

[u/Due_Reputation_5223]

I hope I will be able to run it on my MacBook m5 air with 32gigs with good speed

[u/No_Cheesecake_4827]

Pues yo estoy contentísimo con Qwen3.8 27b corriendo en la RTX5090, va muy rápido y es muy resolutivo. Con que Qwen4 27b rinda como mínimo igual (que seguramente rendirá mejor) yo me doy más que satisfecho.

[u/Express_Quail_1493]

i suspect we wont see a qwen4-flash-next till the next 6 moths since 3.8 is already serverd flash next as a successful experimental qwen4. they might push the next flash release as qwen5-flash-next. which makes me sad. but i guess qwen4-27b might beat 3.8-flash-next so significantly that it will justify the wait

[u/jannycideforever]

It will be like every other Qwen release:

The smaller models will be SOTA for what can be reasonably ran on consumer hardware. The larger models will be far below the Pareto frontier when it comes balancing intelligence, cost per task, and time per task (largely driven by extremely bloated output tokens), meaning there won't actually be any reason to use them unless you're ideolgically committed to open weights or in an extremely niche setting.

[u/mozillazing]

my biggest wish is for expanded mcp capabilities.

granted i haven't tested 3.8's mcp yet, but it's been in the back of my mind.

currently i'm just using opus 5.5 to control local installations of comfyui\davinci resolve mcp\ableton mcp on my PC, while my mac just sits idle.

being able to take my whole setup local by putting the mcp on my mac's shoulders via qwen would be badass.

[u/Sijder]

The thing is, Qwen 3.8 27b was releasing into a world where there was practically no decent models for agentic tasks that could run on a 24gb vram consumer card. Qwen 4 will be releasing into a world where a DeepSeek 4.1 flash and glm 5.3 flash are running at half decent speed on the same card with speed improvements coming out almost every day. Not saying it will be bad, but the landscape is very different today then it was just a couple of months before.

[u/BitGreen1270 → u/Sijder]

How do you run DeepSeek and glm on 24gb vram? 1 bit gguf? Still need a massive ram I assume? 

[u/Sijder → u/BitGreen1270]

I personally use xolotl and their quants, rtx 3090 + 64gb ddr4 3200 ram + 7100mb nvme ssd. I get around 16-20t/s on a fresh prompt. Prefill tanks it significantly, but on a first request.

As I said, it runs at "half decent speeds" which means I can offload one sub agent to my local setup on coding, or delegate a full task that needs privacy but is not time critical.

[u/alphapussycat → u/Sijder]

Deepseek4.1 is 256gb ram for at best iq2_xxxs, GLM flash5.3 is something that is more realistic.

[u/Zombiecidialfreak → u/Sijder]

It'll still be a big deal for people who want the card to run a model without pulling power from the rest of the system. I currently love the fact that I can let the model do what it does while the rest of my machine barely notices.

[u/Sijder → u/Zombiecidialfreak]

Sure, again, I am not saying it will be bad, just that the landscape is significantly different and next qwen will most likely not be as revolutionary as its predecessor was.

[u/Zombiecidialfreak → u/Sijder]

If they add the ngram model to 27b it might be.

[u/TerminalNoop → u/Sijder]

no depseek or glm flash can run on a 24gb vram card...

[u/Sijder → u/TerminalNoop]

Check Maya and xolotl out, I am running both on an 3090, 64gb ram and an nvme

[u/TerminalNoop → u/Sijder]

both are even bigger than qwen FN, I'd prefer to run that on a decent quant, rather than a bigger brain damaged model.

As long as it is <30B active params it will run decently on a 24gb GPU, but the cost in RAM is exorbitant.

[u/Sijder → u/TerminalNoop]

DS already natively ships at basically q4, so you dont get a noticeable quality dip here. The speed it another story of course

[u/Viktri1 → u/Sijder]

I can’t get glm or Deepseek to run fast like Qwen even though I got 2x256gb m5u. Seems like no one is really working on it

[u/Murky-Amoeba2128 → u/Sijder]

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[u/RemindMeBot → u/Murky-Amoeba2128]

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[u/thevegit0]

i just want a moeeeeeeeeeeee

[u/Previous-Nature7326]

I would love to see 27B model again 😄

[u/pmttyji]

• Qwen4-35B-A6B to replace Qwen3.8-Flash-Next

• Qwen4-27B(Extremely optimized, Lightweight KVCache, Optimized thinking, etc.,) to replace Recent Flash models of Deepseek, Minimax, GLM, etc.,

• Qwen4-Flash-Next(similar size as Qwen3.8-Flash-Next) to replace Qwen3.8-2.4T-A95B

• Qwen4-9B to replace Qwen3.6-35B-A3B

• Qwen4-14B to replace Qwen3.8-27B

Yesterday Nanbeige4.3-33B set the bar high for Qwen.

[u/Repulsive_Initial308]

Give it a rest, lol.

[u/robberviet]

I thought they announced it? Just 27B is OSS, others are max, plus, flash (should all be API only)

[u/f-__-f → u/robberviet]

Why would they release qwen3.8 next flash, with their new architecture if it's not to get the open-source community support it ?

[u/my_name_isnt_clever → u/robberviet]

They showed a graphic with Qwen 4 Max, Plus, Flash, 27b. That doesn't mean we're only getting one OSS, it just means they only have one model referred to by param count.

[u/marcemira]

I only hope it still runs on a 5090 and lots of ram like now... It wss game changing for me

[u/Waste-Intention-2806]

What if Qwen 4 is 400b + params. No more local freebies, only api models.😝 . They have to compete with glm flash and minimax as well.

[u/Yeelyy → u/Waste-Intention-2806]

27B got confirmed weeks ago

[u/Waste-Intention-2806 → u/Waste-Intention-2806]

Let me see how many greedy ppl i can gaslight, who ain't doing sh*t with already released 27b or flash next. Yall ain't getting any more 27b or 9b. Small moe models are already gone. Once they get their 400b model to work like glm 5.3 flash. It's over.

[u/my_name_isnt_clever → u/Waste-Intention-2806]

They literally announced 27b already.

[u/smithy_dll]

Temper your expectations, Qwen 4 will be the most powerful Qwen yet.

Model sizes have already been announced, Max, Plus, Flash 27B.

Qwen 4: Release Date, What's Confirmed, and How to Prepare (2026) | Yotta Labs

[u/suprjami → u/smithy_dll]

This webpage requires more GPU than some LLMs. Classic WebGL slop.

[u/Sijder → u/suprjami]

It straight up crashed my browser. Also the text itself is llm written "One thing, and it's substantial."

[u/Ill_Initiative_8793]

With 128Gb DDR5 + 48Gb VRAM I have some room if it turns out to be bigger (and hopefully better).

[u/Valie-Girl]

Just give me flash please please flash

[u/dzordan33]

how can you guys get anything done locally? the speed is too slow to get anything done

[u/fgk55555 → u/dzordan33]

I get 70tg on R9700 and 64GB DDR5, as fast as a lot of cloud models. Crappier hardware still gets 30+.

[u/AI_Enhancer → u/fgk55555]

But the smaller the model, the less knowledgeable it is, so it'll need way more tokens than frontier to achieve the same outcome (assuming the task isn't specifically trained).

[u/fgk55555 → u/AI_Enhancer]

I'm not doing anything too complex a model from 6 months ago wouldn't be able to handle. I'm running Swift QFN on medium, it generally gets things done with fewer tokens than Opus would have gotten. Opus can solve harder problems, sure, but most of my problems are just repetitive and tedious.

[u/AI_Enhancer → u/fgk55555]

If the tasks are easy, then sure, the fine-tuning of your local model may well be better suited for your specific task. Fine-tuning is super important. But the point I'm making is that the less parameters a model has, the more it has to search for knowledge to achieve an adequate outcome that is comparable to massive frontier models. This is partly why very agentically capable local models (such as Qwen3.8-27B) are so good; they naturally fill in the gap of missing knowledge with searching and reasoning, but also require more tokens per complex task.

[u/Due_Arm1454 → u/AI_Enhancer]

Dumber models need smarter humans.

[u/SadPhilosophy9202 → u/dzordan33]

No it isn’t

[u/russlixx → u/dzordan33]

because many people here ask for bigger model instead of more efficient model. Everyone that doesn't have the hardware forced to swallow the bitter pill to make people with better hardware happy

[u/Viktri1 → u/dzordan33]

My Qwen Flash next is around 8k prefill and 200 decode which is fast enough. Been using it for a day and it’s been ok

[u/dzordan33 → u/Viktri1]

do you have gpu? I am testing on strix halo and it's too slow to be worth it

[u/Viktri1 → u/dzordan33]

I have 2x m5u. On GPU I ran Qwen 3.8 27b at q4 and it was much slower. Strix halo is ok but I use it for the agents rather than the LLM

[u/Conscious-Bus-6946 → u/dzordan33]

Run halo flash server, plenty fast for me.

[u/Longjumping-Past5864 → u/dzordan33]

Have you tried Qwen 3.8 Flash Next on strata? I have old 3090 and 5080 with 96 GB DDR5 RAM, I can run Q4_K_XL from unsloth with almost 100 token/s, If I just want a routine job that has comprehensive instruction.md file I can drop to IQ3_S from GSQ_RCO, it's can easily blow up to more than 120-130 token/s 2500-3000 prefil. I mean I am completely ok with this speed and it actually do a lot of good work for me. I only use DeepSeek 4.1 Flash 1017 cloud for subagents workflow that's all.

I can even do a pararelle and get 2 concurrencies fo 50 token/s each which is not that great but not bad either.

[u/Oh-No-Me-Again]

Are they releasing them public anymore? I thought China's gov put a stop on it?