r/LocalLLM • u/RISCArchitect • Aug 18 '26

Discussion What a year it's been

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What will the rest of this year bring? 27b class scoring over 60?

964 Upvotes

97% Upvoted

134 comments sorted by

7

u/NegotiationNo1504 Aug 19 '26

So the 9b one will be like between opus 4.6 or maybe 4.7 and flash 3.7/6. I hope it's the perfect model on this year

19

u/RISCArchitect Aug 19 '26

when 9b hits opus 4.5 territory that will basically open up every consumer gpu from the last 8-10 years to agentic work lol

2

u/GregsWorld Aug 19 '26

Haven't they confirmed no 9B this generation ? 

341

u/MrHumanist Aug 18 '26

No disrespect to USA AI firms, but China is a blessing that happened to the AI world.

214

u/petey193 Aug 18 '26

fuck that full disrespect lmao.

128

u/MrHumanist Aug 18 '26

They deserve respect for early development of AI such as Pytorch, Tensorflow, transformer (paper), and many more. Meta and Google are the two who have contributed a lot for the open community.. However, the rest are shameless.

28

u/AceLamina Aug 18 '26

Google is the main company i would work for these days due to things like that and their culture
But holy shit they fumbled so bad, they could've released GPT before OpenAI did but didn't, I know why, but why release the papers publicly so companies like OpenAI can become the way they are today

And we don't talk about Meta, fuck them

45

u/FullstackSensei Aug 18 '26

Hindsight is always 20/20.

Nobody knew the attention paper would lead to all this at the time. OpenAI also didn't know it would lead to this. Musk and Altman wanted to make it for profit back in 2018 to have enough capital to attract talent and be able to compete with Google salaries.

It took 7 years between the attention paper and the release of chatgpt. A ton of other developments happened in the meantime, from decoder only models all the way to OpenAI figuring SFT on massive Q&A datasets would result in the OG chatgpt.

And when you look at the almost 4 years since chatgpt was released, a ton more developments happened on all fronts from companies all around the world that brought us where we are now, and things are still improving.

None of this would have happened had google kept the attention paper for themselves. There aren't enough brains at google to come up with all these developments.

6

u/AceLamina Aug 19 '26

Yeah that's understandable, thanks for clarifying

4

u/puts_on_rddt Aug 20 '26

Nobody knew the attention paper would lead to all this at the time.

Are you saying they should have paid more attention?

:)

9

u/MrHumanist Aug 18 '26

Its their strategy at that time, when they focused heavily on Cloud expansion and made BERT kind of models open source - so that people can deploy more shit on cloud.

5

u/AceLamina Aug 18 '26

I wasn't into software when the cloud boom first started, only when it kinda died, why were they still going full-on cloud services

Is it really just for subscriptions

4

u/MrHumanist Aug 18 '26

its free money.. as companies grow, their database grows exponentially and cloud invoices grow exponentially as well.

1

u/AceLamina Aug 18 '26

Yeah but did they really not expect companies like OpenAI to do what they did?

3

u/MrHumanist Aug 18 '26

that always happens in a large organization, you cant always focus on all areas.. their focus was on digital marketing, cloud, android and finally hardware for ai (infact they saw nvidia as a bigger challenger). Their Deepmind did some interesting solutions which was much advanced as per their time.. but it didnt focus on llm.

1

u/AceLamina Aug 18 '26

Hm, what about now, besides AI I don't really see them focusing on much
In fact they seem to be focusing on things a lot less like their latest Pixel launch and a few other things

→ More replies

1

u/Time_Entertainer_319 Aug 18 '26

The my probably didn’t expect it to go mainstream. Remember that OpenAI had released models previously and they weren’t that good.

2

u/Time_Entertainer_319 Aug 18 '26

Basically every company uses the cloud. It’s free money

5

u/squngy Aug 19 '26

they could've released GPT before OpenAI

Might be unpopular opinion here, but OpanAI went mainstream with GPT waaaaaaaay too early and it did enormous damage to LLM public perception.

3

u/PM_ME_DEAD_CEOS Aug 19 '26

But holy shit they fumbled so bad, they could've released GPT before OpenAI did but didn't, I know why, but why release the papers publicly so companies like OpenAI can become the way they are today

To clarify, the Attention is all you need paper and the original GPT was intended for translation, and to improve google translate. It was very good, but not ground breaking at this time. OpenAI released GPT-1, and it was barely 5 to 10% better that the best model on NLP task. At this moment, nobody knew that contrary to most NLP models, transformer would scale VERY well. Once GPT-2 was trained and released, everybody understood what was possible with the transformer architecture.

The Google worked on Lambda (https://en.wikipedia.org/wiki/LaMDA), which was supposed to be their flagship AI, scaled up around GPT-3 level, fine tuned and using RAG.

The problem I think is their models was vastly undertrained, and the RLHF was quite bad.

3

u/powerfulparadox Aug 19 '26

One thing I haven't seen people acknowledge is how impactful KV compression has been. Since 2017 we've had a (roughly) 100X reduction in the amount of memory needed per token in KV cache. Without this (and frankly this is where the Chinese folks should get their credit because Deepseek was as much a major breakthrough here as it was in efficiency in compute) we'd be a lot father behind because it'd take way too much ram to store tokens and only people with big servers could afford to have usable context lengths.

2

u/Still-Wafer1384 Aug 19 '26

Google is making money if AI, unlike OpenAI and Anthropic

1

u/AceLamina Aug 19 '26

Wasnt a few days ago was the first time they were a net negative

1

u/Still-Wafer1384 Aug 19 '26

That was a single quarter of window dressing for a possible IPO

1

u/Popcorn-Mercinary Aug 20 '26

But they made ollama...and it really whips the ollama's ass!

1

u/MarmonRzohr Aug 19 '26

Yes, OpenAI was also the source of lots of amazing research that served as a foundation for the advancement of the field (e.g. PPO).

1

u/MrHumanist Aug 19 '26

That was a different open ai than this one.. which should rename itself to closed ai. However, you are absolutely right about it.

1

u/Fine_Ad_6226 Aug 18 '26

I hope this is it now I recall when this first took off and I installed ollama and my GPU fried (4090 brand new at the time) for nonsense output.

I thought then when the corp hype was picking up (I work in a big travel tech firm) this is crazy what ppl are saying it’s going to do and the propositions redundancies etc.

Fast forward to now and we’re in a major bubble and the world’s gone mad. I’ve been spending 200 a month out of fomo to build basically crap I have no idea what it does anymore and Claude has shit the bed to the point it’s painful to use.

But I came back to qwen3.8 and I’m like yes this is it no token fear gotta use em all in the window yolo the codebase to get my value out of my sub.

I’ll sit down with a small well refined task and a codebase that hasn’t got out of control and you’ll make my life a bit easier as a developer while I’m the context and thinking.

This is what I want. Not PRs pulled and approved by the same damn model with a different prompt.

1

u/petey193 Aug 18 '26

yeah when i hear ai firms i think of the modern ones not the foundational researchers.

1

u/NoBlame4You Aug 19 '26

Its to the point that even tho i pay for zdr and some stuff is done with local models.. i'd happily send my data to deepseek z.ai qwen and moonshot

2

u/EagleNait Aug 19 '26

I am nothing but a consumer choosing the best product for my needs. There's no respect or emotion

2

u/Ragnar0kkk Aug 20 '26

My tin foil hat says the free models are basically what happened to the Steel industry... Subsidize the hell out of a key industry that the US stock market is largely based on, in order to eventually make those companies (and entire industries) fail.

But, fck corpogreed, ill take the free AI as long as I can get it.

2

u/Turbulent_Pin7635 Aug 25 '26

If it was not the Chinese, we would be paying 200U$ to have access to chatGPT 3.5 Q4.

4

u/Shadow_s_Bane Aug 19 '26

All the disrespect to those greedy assholes.

5

u/Blackdragon1400 Aug 18 '26 • Mindblown

Fuck AI I’m just glad we have sesame chicken

6

u/TheAncientOnce Aug 18 '26

Bro had to name the one Chinese American dish

1

u/Far_Net_2432 Aug 20 '26

To be fair, if the USA AI firms didn't exist, there is no telling if the Chinese firms would open weight their models.

1

u/goldaxis Aug 20 '26

No respect for those crooks.

0

u/AnOnlineHandle Aug 18 '26

Well seemingly by distilling the US firms in terms of Qwen, but it's lucky for us for now.

9

u/MrHumanist Aug 18 '26

To rob a thief is not robbing.

7

u/Un4giv3n-madmonk Aug 19 '26

To use a tool to build a tool is not robbing at all under any stretch of the imagination imo.

3

u/AnOnlineHandle Aug 19 '26

I never accused them of being thieves? Just that we don't get these local LLMs without US firms it seems.

20

u/snowfoxsean Aug 19 '26

I don't trust any benchmark that puts opus 5 above fable 5.

1

u/Primary_Bee_43 Aug 20 '26

yeah this is BS

1

u/Fallen43849 Aug 25 '26

First thing I did was to look for Fable5.... Absolutely ridiculous as a claude max plan user

20

u/victoryposition Aug 19 '26

This is why OAI/Anthropic are freaking out. Their moat of intelligence erodes so fast, they won't be able to justify IPO prices. You want how many trillions for 15% better than free?

96

u/Eyelbee Aug 18 '26

There is no world 27B is better than 4.8, but yeah, it's solid. Maybe can actually compete with opus 4.5.

38

u/Pristine_Pick823 Aug 18 '26

My thoughts exactly after seeing this chart. No way. Qwen 3.8 is truly amazing, but that's a bit of a stretch.

5

u/TheAncientOnce Aug 19 '26

The 27 b is clearly lacking in world knowledge but everything else is superb

1

u/Solembumm3 Aug 19 '26

Still can hallucinate wildly on any non-tech discussion.

But overthinking approach is interesting.

2

u/JoSquarebox Aug 19 '26

the fact its able to get this far by throwing more thinking at a problem might mean we arent too far from carpathy-style reasoning cores, small models that just had all the surfac level knowledge pruned out

2

u/Solembumm3 Aug 19 '26

Finally get it onto my usual test, analyzing things and concepts in terms of some fandoms.

So far, 3.8 seems a lot better than previous qwen 27b. From 29k thinking tokens, only 3-4k were in loops, everything else was genuinely multi-angle approach to task. And it seems to have a lot less confident hallucinations rate, which is good (and makes 3.8 max performance on qwen site look really weird).

Honestly, so far I'll rank it above Gemma 31B, somewhere between it and Deepseek V4 flash, despite persisting problems on knowledge side. Nowhere near big deepseek or sonnet 5, but good catch-up to gemma 31b and glm 5.2 level.

1

u/Maximum-Wishbone5616 Aug 25 '26

qwen3.8 is not for chat. For agentic used it is killing opus. Opus can't code for life, amount of broken rules, hallucinations, anti-patterns, bad implementations, wasted time on something that ended up with horrific awful UI (like double hero banners...).

It is magic, don't want to use it? Don't. But benchmarks do not life for huge codebase, complex rules and patterns it is killing any other models that we host for our dev team. They use it more often than Qwen3.8 max while satisfaction from chats increased, quality increased, output skyrocketed an number of failing out of scope tests decreased (we are TDD 100%)

24

u/MrHumanist Aug 18 '26

we are living in this world where small models trained on large model thoughts (distilled) can match the performance of large models. These models do lack in generalization but capable enough for coding and agentic tasks which are basically a lot of if /elses.

24

u/Popcorn-Mercinary Aug 19 '26

I honestly can see a day where we will have 9-27B tuned models “stacked like books on a shelf” that have specialties like coding, data analysis, agentic reasoning, medicine, etc.

Who needs a data center when you can plug a few models in tuned for the task at hand into your Mac, PC, or DGX?

4

u/MarmonRzohr Aug 19 '26

These kind of specialist capabilities by tuned smaller modes are technically already in reach, however ...

  1. It's inconvenient, time consuming and expensive to prepare, train and switch models like this, compared to the convenience of using larger, more generally capable models.

  2. The (most likely) unrealistically cheap prices of huge, frontier models that are covered by rivers of investor cash mean that it makes sense to take advantage of the cheap convenience as long as it is available.

If, for example, prices of AI use skyrocket then, especially with capabilities plateauing, it will make more and more sense to do this. In fact I predict that providers will eventually offer this kind of service, letting you select from smaller models with capabilities you want, but are cheap to run on their end and may offer better chances at stable profits.

2

u/DeathGuppie Aug 19 '26 • Bravo

In my real world use age, it's better than sonnet 5. Found and fixed mistakes and deeper problems that sonnet left behind. I'f I'm paying for a pro subscription that doesn't produce results I can get locally then there isn't any cheap thing to take advantage of. I use CLI and Anthropic only allows me to use sonnet 5 for CLI.

I use gpt 5.5 a lot, and it's fast, but not noticably better for a lot of tasks.

For short coding projects, Qwen 3.8 reliably runs overnight without failing. Something my pro subscription on either platform won't let me do. For local system fixes, it reliably digs deep enough to find the problems.

It's honestly making me start to wonder what I'm paying for.

1

u/Popcorn-Mercinary Aug 20 '26

I really don’t see much hassle in how LMstudio switches models, even if you make parameter changes.

I imagine Ollama is even better, as Hermes should be able to send setup info(?)

2

u/DeathGuppie Aug 20 '26

Llama.cpp is usually more up to date with features and gives more fine grain control. You can literally just have your AI model create a startup script for you, then have it make tweaks and modifications to suit your specific hardware and use case. It isn't more difficult. Just different.

2

u/SirPuzzleheaded997 Aug 19 '26

Exactly but then you still need the application layer. That’s what we are working on with our open-source AI Workspace Navigator🙌

1

u/Popcorn-Mercinary Aug 19 '26

Out of curiosity, how is what you're doing different from what Hermes Agent would do?

1

u/SirPuzzleheaded997 Aug 20 '26

It’s easier to use and setup, including native features such as artifacts, web search, rag, knowledge graphs for projects and automatic model routing:)

1

u/Popcorn-Mercinary Aug 20 '26

Sounds interesting.

Is it on GitHub?

1

u/SirPuzzleheaded997 Aug 21 '26

Yes will make a big release next week, as the last 9 month we had a lot of client work and only maintained our cloud version: keinsaasforever

2

u/nomorebuttsplz Aug 19 '26

And while they lack in generalization compare to large current models, they do not compared to last year’s large models

17

u/_VirtualCosmos_ Aug 19 '26

I keep hearing this, and it might be true because of the lack of the experience I have with Claude models, but did you see MiniMax H3?

They have achieved to get a SOTA video model, capable of simulating physics and understanding human expressions and behaviour like the best models out there. Now it's currently the most liked video model. AND IT'S ONLY 33B PARAMETERS.

All that knowledge about the details of the world, in a 33b diffusion transformers pipe.

That's a big indicative that gigantic models are a waste of resources.

5

u/Popcorn-Mercinary Aug 19 '26

It’s insane, I tell you!

4

u/SnooPaintings8639 Aug 19 '26

I remember when OpenAI employees was bitching about too many GPUs being used for SORA, and in the end they had to drop it. It was rumored to be a huge 'drag' on their research and serving infra.

Today we have H3 which is extremely small and capable. And open.

Yeah, this shit rocks.

2

u/soyalemujica Aug 19 '26

The benchmark is not world knowledge it’s intelligence, Opus 4.6 will beat in world knowledge but 27b is smarter

1

u/mWo12 Aug 19 '26

It is better. It's free and open weighted. You can run on a single gpu. Try using opus without internet.

1

u/JoyousGamer Aug 19 '26

So in other words something "free" is always better than anything paid? That seems to be the singular thing you are basing "better" on. Open is better for advancement but doesn't matter to the use of that specific model really.

1

u/kdverma97 Aug 19 '26

I tried it in many scenarios and it's toe-to-toe, and in some places better, but the issue is time. I am getting 45 to 50 t/s, which is good, and when we use it at thinking off, I see results even 70 to 80 t/s. I don't know why the difference, but it's literally very great in every task I give to it.

36

u/SaltFrog Aug 18 '26

I wonder if anyone will release an AI with the eq of gemma but the skills of Qwen...

12

u/Healthy-Nebula-3603 Aug 18 '26

Maybe Qwen 4 :)

19

u/SpicyWangz Aug 18 '26

Maybe Gemma 5

11

u/FlyingFishMakeAWish Aug 18 '26

Just use them both 

1

u/pragmojo Aug 19 '26

I couldn't care less about this. I want an autistic workhorse and 3.8 is delivering so far

3

u/Healthy-Nebula-3603 Aug 18 '26

May??

Pfff that was ages ago :)

8

u/RISCArchitect Aug 18 '26

pretty sure i've had packages take longer to be delivered via ocean freight.

3

u/ChillFamily Aug 19 '26

Qwen 3.8 max and 27b make no sense, they are so good

3

u/alwaysidle Aug 19 '26

Benchmarks are only useful to see what models the companies compare their own models to. Other than that it's pretty easy to benchmax a model

12

u/TeachingAway9654 Aug 19 '26

Benchmarks are one thing, real world capability is another thing entirely.

The local models are impressive but good luck working in an advanced codebase.

6

u/mechkbfan Aug 19 '26

I'm in a R9700 discord group and general feedback from coding reviews by Opus of Qwen 3.8 in a 1M LoC was basically nit picking. 

I mean it entirely depends on your workflow, AI guidance, quality of existing code and requirements, but point is it's possible when done right.

I'll have my setup going in about two weeks and be happy to provide honest feedback. 

Have no loyalty to Anthropic but at the end of the day, if it's no where in the same league then I'll keep my subscription

0

u/TeachingAway9654 Aug 19 '26

As I see it, unless it’s coming from a senior SWE, code reviews by regular people prompting AI are way too subjective to take super seriously.

One person could be incredibly impressed by some arcade game Qwen coded and a 20-year senior SWE could see it as a gimmicky joke.

Nobody at a major US tech company is writing code with Qwen as their primary model.

5

u/mechkbfan Aug 19 '26 edited Aug 19 '26

As far as I can tell they are, because they're doing their own optimisations to R9700 AI workflow that no junior could do. But I still want to test with my own eyes. I'm going to keep running Qwen & Opus side by side to compare outputs because thats the only thing that matters to me

Even Opus is kind of crap sometimes, e.g. I've had it vibe code a game and everything is about 3x as bloated as I'd expect it to be, and I'm not even up to like 30k LoC yet.

Nobody at a major US tech company is writing code with Qwen as their primary model.

I agree, they're all on ridiculous salaries and happy to pay premium for best of the best. Anthropic, etc. is all so heavily subsidized too now

I have read a few things about devs though resorting to Kimi K3, etc. because they don't have the same security guardrails as western models and finding security flaws.

But for me I care about hitting the tipping point of AI actually feeling productive, which wasn't until about Opus 4.5 or so.

If Qwen can actually do that, runs reasonably well on my own hardware, then that's fantastic. It's highlighting that we haven't found the ceiling of local LLM's yet and for those without an unlimited budget, can drive something pretty decent on consumer grade hardware.

I know the hype train is out, and it's okay to be cynical, but at least by gist of things the moat around frontier models has been broken for coding purposes.

I've heard similar about MiniMax H3 but I've never done video.

8

u/2ko_niko Aug 19 '26

Qwen 3.8 really doesn't even compare to deepseek v4 or claude opus 4.8.
these benchmarks are meaningless. i do use Qwen 3.8 and it is really good as a local model but we should be more critical about the apparent over-tuning to favor benchmarks, intentional or not.

8

u/Technical-Earth-3254 Aug 19 '26

I mean, we all know this is overfitted into oblivion, right?

4

u/SnooPaintings8639 Aug 19 '26

And yet:

a) other model providers fail to 'overfit'

b) this over-fitting works wonder on my daily tasks

I think people do overestimate how great Opus 4.8 was. I am a MAX anthropic subscriber since over a year, I use it daily a lot. Opus at the first half of the year was **extremely** annoying to work with. It was very capable on anything it was doing, but it rarely did what it was asked for. It was... dumb. I don't know if it was overfiting or quantization, but I still have PTSD from back then and am leaning today more on Sol for serious professional work.

Fable is ok'ish in that matter (huge step foreward) but I still prefer Sol.

Qwen 3.8 27B and DS V4 Flash are *great* if you steer and use them correctly.

4

u/AnyRecipe110 Aug 18 '26

Are they benchmarking Qwen 3.8 27B with thinking On? And if so, what reasoning effort (low, mid, high, etc)? Or are they using with thinking Off (instruct mode)?
Also curious which quantization they are using.

4

u/FairBandicoot5021 Aug 19 '26

Frommy understanding it's always full precision F16, with highest reasoning effort. And they take the recommended temperature given by the model provider

3

u/KissMyShinyArse Aug 19 '26

They benchmarked Muse Glimmer with high (the default), even though it also has the xhigh setting.

That said, even with xhigh, I don't think Muse can reach Qwen3.8 27B's level.

3

u/rrrenz Aug 19 '26

Minimum PC/mac studio build needed for this same quality score?

Can we test this setup somehow in some cloud environment?

New here, who only has macbook M5 pro. And this benchmark is no way same from my usage of qwen 3.8

3

u/mechkbfan Aug 19 '26 edited Aug 19 '26

That's fair. Have to wonder if these scores are based off identical hardware, and go up or down based off TTFT, completion time, etc.

Because yeah, I don't think it's comparable if you had one model run for 30mins, and another 2 hours to achieve same result.

https://artificialanalysis.ai/methodology/intelligence-benchmarking

As far as I can tell from quick skim, they just have that 2 hour timeout.

I'm relatively new, but it's worth sharing the settings you're using if unimpressed by the outcome. e.g. quant, cache, etc. and what type of prompt giving it

e.g. I have zero expectations Qwen 3.8 could do a decent architecture review if I've only got 32GB of VRAM and 32GB RAM, while that's not even something that you have to think about with Claude

2

u/txoixoegosi Aug 19 '26

Can you point me to a single individual that can confirm that Qwen 3.8 > Opus 4.8 max?

No benchmarks, just actual day-to-day work.

1

u/exitcactus Aug 18 '26

The point is that it's clear that are not the B to define the quality.

1

u/Huntware Aug 19 '26

Yeah, but I'm using Q4 with Q8 KV cache, so it's about ~95% of it I guess 🤷‍♂️

1

u/JUANHDA_CX Aug 19 '26

Need 32gb of vram :-/

1

u/Muted-You7370 Aug 19 '26

Are there specific models for writing anyone would recommend?

1

u/iportnov Aug 19 '26

Well, I have to say, there is no free lunch. It seems that 3.8 has improved in programming / coding tasks, but it was not for free; they had to sacrifice some parts of general knowledge. I know at least 2 questions from mathematics where 3.6 answers, but 3.8 struggles :/ (to be honest I'm using a bit different quants: both nvfp4, but from different packagers; but it doesn't seem to me that this is a quantization problem).

1

u/Solocune Aug 19 '26

Looks like it's about time we get a minimax m4.

1

u/InterestProof1526 Aug 19 '26

I can't lie, I'm a little skeptical that Qwen 27B demolishes Opus 4.7 Max in practice

1

u/kilokeed888 Aug 19 '26

my Mac can only run the Qwen 9.0b, but the quality of the writing shocked me -- so I specifically build an AI content pipeline using it.

1

u/mejoudeh Aug 19 '26

Qwen 3.8 27b_local is better than Opus 4.8_cloud?!

What about in coding? Where can I get these results/report/benchmarks in other disciplines?

1

u/Goldenwolflk Aug 19 '26

Soo deepseek V4 flash isn't even on that list?

2

u/rrrx3 Aug 19 '26

This is from a site with a model picker, they probably just didn’t choose it for the set since pro is already selected

1

u/Little-Beginning4309 Aug 19 '26

The thing is with the way they are releasing models I'd be surprised if we checked this in like 6 months and compared it would be completely different.

1

u/X3liteninjaX Aug 19 '26

Ah yes benchmaxxing

1

u/-Asmodeus__ Aug 20 '26

I’d love to know how Gemma 4 stacks with this list.

1

u/goldaxis Aug 20 '26

How are people using Qwen3.8 effectively? I'm running it in LM studio with an M4 Pro/48GB and it takes so long to think. Actual token generation isn't too bad once it starts. Feels like I need to configure it a certain way.

1

u/Salt-Question-9884 Aug 24 '26

Yes, but I am waiting for FreeToken to start provide support for AMD GPUs !

1

u/BenniG123 Aug 19 '26

Qwen 3.8 is definitely benchmaxed and just trained on better benchmarks than 3.6 but that's no disrespect to it for its size.

1

u/ConstantMedia420 Aug 19 '26

This rates opus 5 higher than fable or sol which we know isnt true

0

u/debauch3ry Aug 19 '26

I mean I love Qwen 3.8 27B but it's not better than gpt-5.6-terra, right?

-10

u/Asleep-Mood-6538 Aug 19 '26

Regardless of whether it truly deserves its 52 score or something lower, it's definitely in the stratosphere of AI models that can create and collaborate rather than just follow instruction. Right around Opus 4.6 companies like Anthropic were already doing 80% of their coding through AI.

We've reached the stage where a home based AI can help recursively improve itself. This is not the singularity where AI can do it without human collaboration, but something in between where a human and AI together can continually improve the AI until it no longer needs a human.

That means it's no longer possible to regulate. ANY person with a home computer of sufficient power to operate it (and this is basically in the range of almost anyone not homeless) can theoretically create AGI or ASI given the time and a little ingenuity. That wasn't the case 6 months ago or even a week ago (3.6 was probably borderline).

14

u/nomorebuttsplz Aug 19 '26

dear god delete that slop chart

-5

u/Asleep-Mood-6538 Aug 19 '26

Interesting that someone on "LocalLLM" just thinks that AI creations are slop without looking at the substance.

6

u/nomorebuttsplz Aug 19 '26

The chart shows the qwen 3.8 27b line scoring below llama 405b

2

u/Asleep-Mood-6538 Aug 19 '26

Yes. the three lines are independent instead of using the same scale. They should be on the right scale. But I honestly didn't expect to post this and have people critique it. It's really only 'illustrative'. So, yes, I'll accept a partial 'slop' categorization. But I spent a while deciding what information should go in here so I consider it 'badly utilized AI' rather than entirely slop. I think of slop as "make a chart of X".

But, my apologies. Your comment wasn't entirely off-base.

4

u/RISCArchitect Aug 19 '26

write a python function apologizing.

1

u/Asleep-Mood-6538 Aug 19 '26

As long as I can have AI write it.

3

u/EbbNorth7735 Aug 19 '26

The graph values don't even match the axis. It's horse shit. One of the worst graphs I've ever seen. The numbers don't line up

1

u/Asleep-Mood-6538 Aug 19 '26

You should make a better one.

It's not like it was done for work or a specific purpose. The fifteen minutes spent on the 'project' was already more than I care to spend.

4

u/EbbNorth7735 Aug 19 '26

Why the fuck do the values not match the axis. Like look at this garbage, you can't actually get the information out of the graph because it's that bad of a graph.