meantime on r/vibecoding
Posted by jacek2023@reddit | LocalLLaMA | View on Reddit | 126 comments
words of wisdom
Posted by jacek2023@reddit | LocalLLaMA | View on Reddit | 126 comments
words of wisdom
Mission_Biscotti3962@reddit
it's amazing for people who know how to write code, it's still useless for people who need something to read their minds and one shit it
false79@reddit
It's not even about writing code. It's about breaking it down to smaller tasks, providing context so that the LLM can connect the dots faster than a human would. Huge gains.
sonicnerd14@reddit
Engineering is becoming a higher valued skill when working with AI, then all the smaller microskills that used to be required on their own like planning, coding, etc.They are all important, but since AIs allows 1 person to effectively do this all simultaneously, the users task now is more about understanding every category at a competent enough level to explain it all. The more information the AI gets, then the more likely it will give you exactly what you are looking for.
juraj336@reddit
This so much, having the model first converse with you what you really want to build and create a spec + plan out of that and then letting new fresh models create said spec via the plan in phases has been so simple to setup and got me great results with smaller models.
I think most people who think these models are useless expect it to just "make a website" when you ask. That just doesn't work.
DavidAdamsAuthor@reddit
"Make me GTA 6"
It didn't do it, worthless model.
SkyFeistyLlama8@reddit
I use different models for this. Usually it's a dense local model or a cloud model to come up with a plan, then I hand the todo list over to a smaller local MOE to come up with the actual code. Tests can also be written up by that local MOE.
There's still plenty of hands on work for me to do as an SWE but that's the whole point. I can't stand the idea of vibe coding: if I'm going to accept everything an LLM plans out and writes, then what the hell am I doing behind the keyboard?
TheIncarnated@reddit
Are you setting up the plan? And itterating? Or do you use a local agentic tool?
Like I have a work flow that does document creation via scripts but I've not thought about the other options
juraj336@reddit
I originally tried both Superpowers and GSD, GSD worked great for Sonnet and Opus but did not perform at all for me on Qwen 3.6 27b
Superpowers however works pretty well! I personally use it only for bigger projects though, especially their brainstorming skill!
But for small home projects, I just ask it to create a spec/plan, then once done I check it and if good ask them to create a plan with 5~ phases and a prompt to give the agent that will begin it.
Then create a new session for each phase (or if you have a lotta vram spawn subagents and give the prompt and voila.
Also extremely handy is to tell the LLM to test whatever it creates in each phase before finishing. It followed that instruction really well.
EbbNorth7735@reddit
It's not this, it's that
sonicnerd14@reddit
Ironic, but you make a good point that with the smaller models you really need to have more knowledge in coding or engineering in general to get the model to properly get a task done.
What I don't quite get is this mentality that even the larger models will perform a miracle with very little information in only one prompt. Like even people dont operate like this, so why would an AI? Unless you have a neural interface of some kind, this will probably never happen.
blutosings@reddit
I honestly didn't expect local models to advance this far by now. I occasionally run into a task I can't really break down effectively for qwen but most of the time it still exceeding my expectations.
cafedude@reddit
I had it coding Verilog (niche, obscure verilog) and after a while it did get stuck with a non-blocking assignment problem. (But, TBH, NBA problems are kind of Verilog's fault - even humans struggle with this) It looped around for a couple of hours trying to figure out how to get out of the corner it had painted itself into. Handed it off to Claude and it figured it out after a few minutes. But given that this is Verilog we're talking about - a very nichey hardware description language - it doesn't seem like something a lot of people are going to run into with this model and the fact that it can code fairly competently in Verilog most of the time is just pretty amazing for such a small model.
DavidAdamsAuthor@reddit
I've done some work in HDL Verilog and to be honest I'm kinda surprised that the VM didn't try to commit suicide immediately.
AI has a lot of way to go before it can imitate humans.
gtek_engineer66@reddit
Where you using the qwen with claude code ?
cafedude@reddit
OpenCode
itisyeetime@reddit
I also write a lot of verilog, which models do you find are stronger at this?
cafedude@reddit
Claude is probably the best. But Gemini 3.1 is pretty capable as well. Right now I'm doing some work with GLM-5.1 and it seems quite capable at verilog as well.
pbpo_founder@reddit
You know if you only have a few brain cells, it’s really easy to have your mind read. 😏☝️
_mayuk@reddit
hahaha great comment xd
Ok-Palpitation-905@reddit
Im still in the learning how to code phase, and its pretty sweet.
Kerbourgnec@reddit
Hey I'm the guy who is supposed to read my boss / client's mind and one shot it.
maz_net_au@reddit
But if you train a model on "dealing with the realities of enterprise" you'd end up with a neurotic mess.
Unfortunately dealing with people and their vague / impossible expectations is best left to experienced people.
Borkato@reddit
Exactly. I’m confused as hell at how people are thinking it’s supposed to be magic??
Themash360@reddit
Some vibe coders have gotten used to the model using many tokens to make a coherent plan out of their incoherent thoughts, they lack the fundamental understanding of a llms limitations because their interaction with one goes through a huge software stack from Anthropic that gives it an enormous leg up that open source is not yet caught up to.
Working with a llm yourself helps built understanding in how context actually works, what it actually needs to hear/not hear, and thus how you should instruct it.
-dysangel-@reddit
You probably already know this, but you can hook open models up to Claude Code just by changing some environment variables/config. It's what I've been doing the last few months. GLM 5.1 + Claude Code gets the job done for me every time.
Themash360@reddit
I was not aware, I will definitely try this
sciencewarrior@reddit
Be aware though that Claude Code seems to be "tuned" for fairly powerful models. If you are using a local model in the 8B to 27B range, you may see better results with other tools.
a_beautiful_rhind@reddit
Its not magic but larger models understand more.
ComplexityStudent@reddit
Is not magic. But is unlikely that a new vibe coder will ask for something truly original, and these frontier models have a lot of world knowledge, plus the platforms like claude code give them access to RAGs, search engines and such.
So, when a new vibe coder would ask for something standard like "write a Flappy Bird clone", the larger models will have much greater odds of one shooting just by virtue of the amount of information at their disposals.
BubrivKo@reddit
I know how to write a code. I do it for 15 years. I need an assistant that is better than me. Opus is, Qwen is not. I can trust Opus, I cannot trust Qwen.
Mission_Biscotti3962@reddit
I don't want to go into some endless debate but if you really have 15 years of experience and you have extensive experience with llm's you should know you can't trust any of them.
For me the point is not trust, it's speed of execution. Reviewable chunks that are written faster than I would have but that are still manageable for me to verify. That kind of work is perfectly doable with a qwen 3.6. On average I'll probably correct it more than an Opus, obviously, but having it run locally without usage limits is golden
zxyzyxz@reddit
It's almost as if engineering is a skill that's not necessarily related to writing code
smirnfil@reddit
But why would anyone not use a tool that reads your mind if it is available?
FullOf_Bad_Ideas@reddit
if I had to pay API prices for Opus I probably wouldn't use it that much. If API price barely recoups the R&D and real cost is even higher, I'd use it even less.
Price is the main component of the equation. Ethics and open-ness/privacy are realistically secondary.
smirnfil@reddit
Sure, but if we are talking professional software development price of claude premium team seat is minor fraction of the other costs. If/when the price would go higher(like current api price for example) it could be another discussion. Ethics is complicated topic, but it is important not to mix ethics with the real performance assessment that unfortunately happens too often.
tyrannomachy@reddit
Because of what it often indicates. If an expert has to tease out what a client wants, they're not really "mind reading" even metaphorically, because there's nothing inside the client's head that would be coherent enough to "read", even if you could.
What they're really doing is constructing a mental model of what a non-expert who is saying whatever the client is saying might come up with if they had more domain knowledge. But that mostly amounts to guesswork.
At least for me, if Claude or whichever model needs to read my mind, it usually means I don't actually have a coherent idea in my head, even if it feels like I nearly do. Haven't had great luck in those situations.
smirnfil@reddit
I found completely different experience - I use very declarative free style in the planning phase. Basically doing brain dump of anything I think about the ticket. With lots of phrases like maybe, suggest, I am not sure etc. In the huge brownfield project with minimal claude . md and docs. Yes I guide it if I see something wrong with a plan and I would never execute any changes in this style, but these "mind reading" capabilites is a huge selling point of the latest Opuses to me.
ComeFromTheWater@reddit
That why you gotta use normie ChatGPT as your Tom Smykowski. Just type what you want, tell it to format as a one shot brief, then give that you your goddamn local model.
gladfelter@reddit
Qwen 3.6 27B proves to me that the hype about LLMs is not off-base. I could see what top-tier LLMs could do for me, but I didn't know the cost side of the equation. Now I see exactly what resources it takes to make a useful coding agent that can improve my productivity signficantly for years and it's a $650 for a used 3090 I bought last year and maybe $0.50 of electricity per day. That's so much cheaper than my salary that I have no doubt that LLMs will be everywhere.
It's certainly possible that cloud providers will over-build; in fact, it's almost a certainty. But the potential value is commensurate with the cost for fully-utilized infrastructure. The larger models and all the investment, plus plenty of engineering can make AI work for people with less experience in bending imperfect tools to their will.
A small and limited but effective model convinced me of all of that, anyway.
GiveMoreMoney@reddit
You said everything I wanted to say, only better than I would have done.
One addition to your comments, it is not only the model, it is the tools. For me Claude is amazing (I am using the Opus 4.7 online, not even Claude Code) and I am amazed from the results. Those results are Model + Tools they have in their services. Would I be able to afford it the way things are going? No, already bought an R9700 and Qwen 27B works very nicely with it.
I will just have to go back to coding full time, like I used to, but this time with the help of Qwen and such local models. The 2 year break is over it seems.
kmp11@reddit
its amazing for people with ideas but do not know how to code.
Mickenfox@reddit
I think optimizing for vibe coders actually makes models worse for experienced devs. It trains them to make assumptions and keep going no matter what.
Mission_Biscotti3962@reddit
I cannot overstate how much I agree with this!
wbulot@reddit
Local models have been wonderful for me, especially since Qwen 3.5 was released. With Qwen 3.6, it's even better. These models are perfectly capable of handling small coding tasks without errors when given the right context and prompt, and that's how I use LLMs anyway, so it's ideal. If people expect the model to think for itself, they will be disappointed with just a few billion parameters. It should be used as a tool that uses the keyboard for you—that's all. You do all the thinking. And that's already a game changer for developers who know what they're doing.
Both_Opportunity5327@reddit
It has excellent SVG generation and HTML single page skills.
-Ellary-@reddit
I remember how Llama 2 guides started with something like "LLMs can't read your mind, you need to master how to guide and prompt it properly", and now people complaining that they don't read my mind and intentions.
This sub was one of the smartest at 2022-2024 LLM era.
Cool-Chemical-5629@reddit
"read their minds" what a funny way to describe the model's ability to comprehend the prompts.
q-admin007@reddit
If you can't speed up your code writing with this model, i question if you can write code at all.
artisticMink@reddit
Despaaaair
EuphoricPenguin22@reddit
I ported 1000 lines of C++ to Rust with a 4-bit quant of a 35B sparse model and you're telling me I'm supposed to be disappointed?
turtleisinnocent@reddit
Right, but did it produce bug free working code? That’s the issue.
EuphoricPenguin22@reddit
Yeah, it did. Obviously I had to manually test it to help it spot issues, but nothing more than "this sounds wrong in this way and I think it's probably a bug in this vague part of the code."
turtleisinnocent@reddit
That's so cool. What quant are you serving? How about the KV cache?
EuphoricPenguin22@reddit
Cache quantization kills performance, so it's usually not worth using if you can offload. I use the smallest 4-bit quant for basically every model I use: the specific one I used is in the post title. Honestly, the secret sauce is a good agent and a good RAG MCP. I mentioned at the end of the post what I'm using specifically, but these models lack world knowledge that larger models have, so it's especially important to insist they reference documentation so they conform to the stated plan.
turtleisinnocent@reddit
100% this is the way
I've found the Sisyphus agent in Oh MY Open Code to be quite effective at hammering the last drop of LLMs, local or not. Not to say thats the _only_ way to go, there's tons of way to do it.
I'd differ on the MCP thing though, I've found the latest batch of LLMs quite capable of writing their own scripts and then running them, calling on command line tools to do their thing. I was getting a bit overwhelmed with MCP hell.
EuphoricPenguin22@reddit
I guess I'm a chronic user of libraries that seem to be almost entirely absent from the training data, then. At least enough that the model would otherwise fail at writing functional code without a RAG system to reference the docs. Heck, I've been using that system with larger models anyway, as it forces the model to write higher-quality, up-to-date code.
90hex@reddit
On point. And that cycle seems to be repeated for every. single. OSS model.
There are genuine use cases for these small models, and they're 100% valid both personally and professionally. The trick is that nobody will say, because it's the nature of business.
For example I started working on a project that automates a very, very common problem on Windows and Mac. It's using Gemma4 E2B, a tiny vision model. For this use, it's fantastic - but I'm not asking it to write code, only as a very basic classifier.
That's where the money is. For everything else, people will stick to their Diet Pepsi (GPTClaudeGemini).
BringMeTheBoreWorms@reddit
It’s a damn beast! I’ve got 35 years of coding background and it’s great. I’ve found Claude stuffing up all over the place, duplicating and going off on tangents, 27b actually stays on target
NoxinDev@reddit
I completely agree - If you know what you are doing I've found both the recent 2 MOE gemma4 and qwen3.6 are able to put out what I am looking for provided some context examples and commented api docs. Running them locally means I don't have the same worries as passing proprietary structure across the wire to some US corp's logs, that's never going to happen with closed models.
The bigger models also seem for an audience of "vibecoders" (egotistic BAs) rather than actual software developers, if I have to rewrite half of it to meet quality standards than it's not a useful tool.
The biggest win for me was actually SQL, being able to report on what I need without remembering the 30 odd joins for the single-worst-database-design-on-earth has saved me serious time.
BringMeTheBoreWorms@reddit
I was trialing a few of the hundreds of agent memory solutions around at the moment, and setup hindsight to see how that would go. Looked nice, but absolutely shat itself when I tried to run it with only local models.
Rather than just try another one, I let 27b have a go at it. Grabbed the source from git, rolled my own docker image and then let it go to town. It fixed all the issues I had.
But if I didnt have a heavy background in software there is no way Id have been able to direct it and get the job done. Ill probably submit the updates back to hindsight soon as they seemed to be pretty fundamental improvements.
iMakeSense@reddit
What are you making?
BringMeTheBoreWorms@reddit
I was building a game engine for me and mates rpg campaign thats been going for a decade or so, but I've been distracted rebuilding out my dev environment for the last few months. Getting my local setup working, then mucking around with agent workflows, memory etc
Its all helpful as a consultant as well, it makes it look like I know more than I really do to clients
asertym@reddit
I've been coding since feudalism and I gotta say this is a game changer.
autoencoder@reddit
So since... today?
AdventurousFly4909@reddit
What I want to is parallel programming with a LLM. The LLM will only do simple things, no hard things or else it will spit out solutions that work but you actually never want to see in a code base. What I use them for is.
Change these function signatures to accept a UUID. Or write error messages at these places. Or a introduced a error to a old function and now the consumers of those functions need to be updated, I will let qwen3.6 27B do those things. I don't want it to do anything else. While qwen is doing those things, I am already debugging or adding some feature. It definitely improves my productivity without sacrificing quality since I still do the thinking myself. What is funny you can see it reasoning over what build errors are his fault or are mine.
cloud models scare me since each time I use them I always have a feeling they will remove a whole section of and then try to rewrite it. No just stay on task.
KrayziePidgeon@reddit
Sounds like a prompting skill issue.
AdventurousFly4909@reddit
I am going to fix my programming skill issues instead of my prompting ones lol
thedirtyscreech@reddit
I’m similar to you, but I’m starting to give it a bit wider scope in my requests. I’ve found this helps a lot. I also added a section on the LLM should always assume it is at fault first. I don’t have that addition in front of me, but LMK if you’d like me to post it later. I also added the graphify skill, which adds a section for that when used for Hermes.
In addition, I make a detailed PROJECT_SUMMARY.md which I make the agent read at the start of any session and update with changes during the session at the end.
Borkato@reddit
This is how I use it too! And bug fixing ofc :3
soyalemujica@reddit
I agree, 27B to me even beat Deepseekv4 in tries I did lol with existing codebase
kiwibonga@reddit
PSA: Right now the official Qwen repos for all 3.5 and 3.6 models ship with a broken template. Most people are still using the broken template that causes massive quality degradation
CircularSeasoning@reddit
I'm using a custom template or two already but, throw a dog a bone won't ya. :)
kiwibonga@reddit
Ask Qwen for this, why ask humans?
CircularSeasoning@reddit
:( Fake PSA. No info forthcoming from this user.
SkyFeistyLlama8@reddit
Where can I get a fixed template to load manually in llama-server?
kiwibonga@reddit
This is the comment field. The search box is at the top of the screen and you don't need to be so verbose.
SkyFeistyLlama8@reddit
Don't need to be an ass about it. This is the first time I've seen anything about broken Qwen 3.6 templates.
Dazzling_Equipment_9@reddit
Although I already knew this was reality, I still have to admire the intuitiveness provided by the graph.
hay-yo@reddit
I think if they release a 122b 3.6 we'll be amazed.
CryptoUsher@reddit
local llms aren't about matching frontier performance, they're about control and iteration speed when you're tweaking prompts or fine-tuning for niche use cases.
instead of asking if they're as good as gpt-4, should we be asking which workflows actually improve when you have a model you can run offline and prod at all day without rate limits?
iMakeSense@reddit
I wish there were more threads like that, or something like a closed survey where everyone whose been subbed more than 3 months could vote in.
CryptoUsher@reddit
totally agree, a vote or poll here would actually be useful. might even help people discover new workflows they hadn’t considered.
CryptoUsher@reddit
tbh i’ve been using llama3-70b and mistral-small for contract work, and the real win is just not waiting 20 seconds for gpt-4 to catch up while i tweak system prompts. feels faster to iterate even if the model’s weaker.
CryptoUsher@reddit
i think a survey could be really useful, maybe someone with more karma than me could make a post to gauge interest in something like that, see if there's enough support to make it happen
Cool-Chemical-5629@reddit
Thanks for a cup of coppee, I needed that in the moment of despair.
CryptoUsher@reddit
glad it helped, man. fwiw, i've been using llama3-8b on my rtx 4090 for prompt tuning and the edit-run cycle is just way faster than waiting on api queues
Worried-Squirrel2023@reddit
the valley of despair phase is healthy. anyone vibecoding for more than a month figures out the AI doesn't actually replace knowing what you want.
Best_Control_2573@reddit
I'm not finding a valley of despair at all. Qwen 3.6 just gets better and better the more I learn to use it. I'm already sitting in the outlook of hope for the next version, and the deep empty well of insufficent GPU funds.
Quirky_Inflation@reddit
Too bad people taking corporate decisions don't know that
droptableadventures@reddit
I think the "we are here" needs to be moved a bit to the right, as the valley of despair got posted yesterday.
jacek2023@reddit (OP)
this repost was my reaction to that cry-post
BubrivKo@reddit
Yeah, I laughed a lot at comments like "Opus model with only the 26B parameter!? I'm canceling my Claude subscription".
How delusional does a person have to be to think that a \~30B model can actually beat a frontier model...
I tried them (Qwen 3.6, Gemam 4) and - no, they are not even close to Opus, Sonnet, and even Haiku, lol. 😃
hwpoison@reddit
People expect the LLM to do all the work, but this isn't how it works, is just an assitant.
FastHotEmu@reddit
is this the peak of slop meme posting?
Nick-Sanchez@reddit
Hey, at least it's better than Minimax, I'm now 10 whole dollars richer every month. Except for the GPUs power consump--- oh fuck... nevermind.
audioen@reddit
I don't know what this post is talking about. The 27b model is genuinely very good. However, I admit that I have no idea what Claude is capable of because I've never touched it, and probably never will. I don't care about cloud models, I care about what I can make my own computer to do.
From that point of view, my life is better than ever. LLMs were all but useless until gpt-oss-120b came out, which was surprisingly quite fast and decent. Since then, models have been more useful than useless, and 3.6-27b is stunningly small compared to what it is capable of. A year ago, I would have thought this performance only exists in datacenter.
I'm pretty happy with the output I can get, and I think future computers all have at least this level of baseline ability because it asks for relatively little, and we're still in the early days of LLMs, with very unoptimized models and architectures, even if these today seem state of the art. It won't be long that nobody cares about this model. But right now, I think it's the top dog, likely only to be beaten by 3.6-122b for my hardware.
Upset-Fact2738@reddit
generally I agree that this model is a beast for local hardware. My post was not about the model itself but more about the people (vibecoders) who expect 27B parameters to perform miracles on par with trillion-parameter SOTA cloud models
-dysangel-@reddit
The chart is sensible, but the text at the end is odd. Parameter count limits potential, but it isn't a good indicator of actual performance. Early Llamas and GPTs etc had lots of parameters, but many small modern models would run rings around them.
switchbanned@reddit
I can't wait for valley of despair
pkmxtw@reddit
It's funny the graph is basically inverted for gpt-oss, which was thought by /r/LocalLLaMA to be the worst model ever conceived because it was released by OpenAI.
shokuninstudio@reddit
If anyone, especially someone anonymous on reddit, claims a sub 100B local model is amazing at x ask them to do a uncut live stream demo with viewer requests otherwise they are not producing evidence of x.
geldonyetich@reddit
Happens with every hot new model really. The initial improvements blow us out of the water. Then reality catches up with our expectations.
Okay, yes, it's a better model but we still need to be diligent about what we're asking for and go through what we get with a fine tooth comb.
MalabaristaEnFuego@reddit
I'm still over here getting positive results with GPT OSS 20b and Qwen 3 Coder 30b. That's not even including Nemotron 3 Nano, Devstral Small 2, GLM 4.7 flash, and Gemma 4.
iMakeSense@reddit
what are you making?
MalabaristaEnFuego@reddit
I use them for mechanistic interpretability coding, and a practice project making an inventory management system.
ruuurbag@reddit
Given 27B's overall competence, the tradeoff between paying for a smarter model and having unlimited usage of a dumber one (for the cost of your GPU + electricity) is one worthy of consideration. It's not Opus, but it doesn't feel a hell of a lot worse than Sonnet and the only measurable thing I lose by having it try again is time.
putrasherni@reddit
now wait for qwen 3.6 9B to be released
iMakeSense@reddit
I don't know what to make of these things. High quants seem to perform well. I think the Q4 quant which is what most lay people can afford to run might not work as well? I'm not sure which benchmarks work to quantify that either as benchmark engineering seems to be a thing.
I saw some comparison posts using websites the other day. The qualitative comparisons from those seemed tangible. Maybe lower peak and higher valley
cbterry@reddit
I follow that sub and it hurts my brain
debackerl@reddit
Can't wait for the Slope of Enlightenment, looks awesome!!
StrikeOner@reddit
its even funnier to see the vibecoder gang with their subscriptions getting milked by a price increase that's 10 fold and they happily pay it since there is only this one model "who is able to understand them". good times!
Far-Low-4705@reddit
actually that last point is:
"eh, next model when???"
sleepingsysadmin@reddit
I know many people who used qwen 3 32b for pre-agentic and kinda agentic. When 27b came out. It was a complete upgrade for them.
So while 32b was completely usable, 27b went well beyond usability.
The question is this frontier, like 1T quality? Perhaps not.
If you're a newb at AI coding. You likely need the hand holding of a 1T model.
If you were a dev pre-ai. These frontier small models are epic tier.
caetydid@reddit
I am actually waiting for all pending optimizations kicking in which will probably double my t/s and my context
Due_Duck_8472@reddit
It is utterly useless compared to fromtier models. Sure, it's good enough to write Hello World.
hugthemachines@reddit
Skill issue.
xLionel775@reddit
That says more about you than the model.
Intelligent_Ice_113@reddit
utterly dumb? - for sure
useless? - definitely not.
Few_Water_1457@reddit
love it
TheSlateGray@reddit
Why doesn't Qwen3.6 27b IQ2_XXS with 16k context write perfect code through Claude Code?!? /s
false79@reddit
Dunning Kruger for LLM's, lol.
I can say I'm at Plateau of Sustainability with gpt-oss20b.
Slope of enlightment with Gemma 4.
I skipped the peak and valley, once you go through it, you try not go through it again.
JuniorDeveloper73@reddit
well looking behind a couple of months 3.6 27b its incredible for his size
Intelligent_Ice_113@reddit
I'm still at the top of "peak of stupidity" 🥰
-Ellary-@reddit
tbh based on my own tests some tasks 27b 3.5 perform better, for example I like how websearch works with 3.5 version. Qwen 3.6 should be called Qwen Coder or Qwen Agent idk. Truth is Qwen 3.6 can't even work as properly as customer assistant, Gemma 4 is way better at this type of usage. All task when you need to "talk" to Qwen 3.6 is falling apart pretty quickly.
ridablellama@reddit
lots of valley of despair posts in the past day or two
bitplenty@reddit
oh wow, I feel smart now, looks like I'm ahead of the curve by about 8 hours!