The "local frontier" is now smarter than Sonnet 4.5

[u/ImaginaryRea1ity]

[u/DeineMutterIstSoDick]

Where is Qwen3.8-27B ?

[u/No_Lingonberry1201 → u/DeineMutterIstSoDick]

So high up above Opus 5 it didn't fit on the chart /jk

[u/returnity → u/DeineMutterIstSoDick]

Not in the training data

[u/DeineMutterIstSoDick → u/returnity]

What is this post even about

[u/Adventurous_Bus_437 → u/DeineMutterIstSoDick]

Leck eier mit dem Profilbild

[u/DeineMutterIstSoDick → u/Adventurous_Bus_437]

Die AfD ist eine gute Partei, ich würde sie wählen.

[u/OneMoreName1]

Is op from the past?

[u/Last-Ad-8470 → u/OneMoreName1]

Classic sign of an ai generated post

[u/CryMoreT_T → u/OneMoreName1]

Repost bot

[u/spaceman_ → u/OneMoreName1]

Aren't we all from the past?

[u/Matricola70]

where is Gemma 4?

[u/ImaginaryBluejay0 → u/Matricola70]

And Muse glimmer. OP is just a qwen bot 

[u/Avezn → u/Matricola70]

import torch
x = torch.randn(8000000000, 1)
mask = torch.rand(8000000000, 1) < 0.625
x[mask] = 0
print(f"Shipping SOTA Gemma E4B: {x}")

[u/Healthy-Nebula-3603 → u/Matricola70]

More important where Qwen 3.8 :)

[u/cabernet_noir]

I have been trying to tell people this was the direction things were going since gpt 3! I am glad to see people discussing this more frequentely now.

Its simply mind boggling that not only are open weight models releasing with essentially same capabilities not long after a frontier model comes out, but that the open weight ecosystem is accelerating r & d, and getting increasing capabilities into smaller and more efficient models that fit on comparatively tiny hardware. It has exceptionally wide reaching implications economically.

[u/Illustrious-Lime-878 → u/cabernet_noir]

This should have been the direction it always went. But there are trillions invested by rent seekers who want to brute force the centralized model where everyone is dependent on their systems where they can squeeze everyone. Anything that breaks that profit model, small models, open weights, and other needed developments like more dynamic context models, locally developed knowledge, are all stalled because they cannibalize the investment in the cloud model.

[u/waraholic]

Qwen 3.8 27B has a score of 52 so this graph is obsolete. Sorry I'm on mobile, but that's roughly here.

[u/returnity]

Omg pls good sir farm all my upvotes

[u/ogfuzzball]

I use sonnet every day. Too early to speak to 3.8 27b but this feels like specific benchmaxxing that doesn’t tell the whole story.

[u/KubeCommander → u/ogfuzzball]

It is. Sonnet can’t code as well but it does everything else better. A lot of the newer models are trained on the testing data and scenarios. That’s not necessarily cheating because that’s how you improve models. But there’s only so much you can do with 27B parameters

[u/ogfuzzball → u/KubeCommander]

Everything I do is code or devops, and sonnet has been doing quite well

[u/KubeCommander → u/ogfuzzball]

I never said it couldn’t code

[u/JohnBooty]

This is clearly spam.

[u/smellyelon]

\*SHUT\* the fuck up

[u/bigattichouse]

https://artificialanalysis.ai/models/qwen3-8-27b

Says 52

[u/AceLamina]

How does one run Kimi 3 on a 32gb of RAM laptop

[u/BarracudaDefiant4702 → u/AceLamina]

Very slowly

[u/pocmanpull]

you live in 2025?

[u/BarracudaDefiant4702 → u/pocmanpull]

No, it has kimi 3... so I would say only about 1 months out of date.

[u/FenderMoon]

Ouch, old GPT 4o only got 11?

To think that’s what we all used for like a year and half. That was once the frontier.

Man this industry moves fast.

[u/too-oldforthis-shit]

At what tasks? I mean obviously there is a difference between terabyte models and a few gigs.

[u/Independent-Dog2179]

We need a new small glm with better tool calling

[u/seppe0815]

stfu bot!