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Qwen 3.8 27B

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Re: Qwen 3.8 27B

#531

Post by culi »

hannofcart wrote: post #525
Balinares wrote: post #248

I wonder if Anthropic and OpenAI possibly missed the window to go public. A 27B open-weight model trading blows with the SOTA from just half a year ago is not great news for trillion-dollar investments...

Another way of rephrasing that though is that the public (including large pension funds, retirees, etc.) just dodged a bullet and aren't left holding the bag. Nevertheless, I doubt anyone's going to emerge unscathed when the valuations start falling though. Vast sections of the American stock market will be wiped out yet and with it the global economy.

Why do you assume 2-3 American companies failing will have a more negative impact on the economy than positive impact of the widespread availability of self-hostable, open-sourced, and efficient models?

There will surely be tons of new companies that make a business off of hosting these models and even tuning them for specific purposes. Not to mention the massive pricing difference will benefit people who actually utilize them

Re: Qwen 3.8 27B

#532

Post by virgildotcodes »

satvikpendem wrote: post #485
gpm wrote: post #459

Earlier quoted context omitted.

I think it's very clear that someone who has checked out all the models but the one that called itself mechahitler and is explicitly being fine tuned to support far-right politics is making the choice for reasons other than performance and cost. It's not like all the other models even had plausible claims to those metrics.

As I said to a dead reply, for coding all of that is immaterial, as long as it codes well then that's all that matters to most people, except it seems those who have an idelogical issue in which case the other model companies also have issues.

The funny thing is it doesn’t even code well. It’s still worse than OpenAI, Anthropic, and the leading open source models.

So you get worse outcomes while also financially supporting one of the most prolific pushers of race wars, the destruction of labor rights, environmental protections, and general misinformation.

Truly a win-win?

Contrary to your framing it seems to only reason to use Grok at this point would be ideological.

Re: Qwen 3.8 27B

#534

Post by bliteben »

stusmall wrote: post #436
hypfer wrote: post #68

Earlier quoted context omitted.

> I've settled on GLM-5.3 (formerly Deepseek v4 pro 0813) for architecting Dude, GLM-5.3 released _today_. The phrasing "I've settled on" is incorrect for this context.

I'm generally extremely skeptical about a lot of the model hype that show up in comments. Except when there is an extreme mismatch the performance, quirks and quality of these things are difficult to nail down. You wouldn't know that from the comment section of every single release . I think some of these are excited, eager users always ready to hype up the new thing. The same crowd that previously would constantly p…

I think most of it is bot driven spam by the various labs. It's hard not to notice 3 month old accounts with very strong opinions about various frontier labs and little else.

Really no different than when there was suddenly online personas everywhere hyping up TSLA out of the blue. You can see the same thing going on with the BoringCompany subreddit. Crazy that the botnet master isn't able to convince us that Grok is also the best model. I don't think buying twitter was an accident it was probably just literally covering up the evidence.

https://www.rhsmith.umd.edu/research/twitter-bots-boost-tesl...

Re: Qwen 3.8 27B

#535

Post by simjnd »

dannyw wrote: post #296
Balinares wrote: post #248

I wonder if Anthropic and OpenAI possibly missed the window to go public. A 27B open-weight model trading blows with the SOTA from just half a year ago is not great news for trillion-dollar investments...

Trading blows in some benchmarks is a bit exaggerated. If you try the model, `xhigh` is basically feels like the `max` mode (i.e. massive thinker and extremely presistent), and the amount of world knowledge and intent understanding is nowhere close to an Opus class model even from 6mo ago. It's still very useful, and it'll probably displace a good bit of API spend; but it's not really "trading blows with SOTA from ju…

Why would anyone rely on the world knowledge built into a model when the harness can just let it search for current information?

Intent understanding is a big point for sure, but world knowledge I'm not sure I see a use case for it.

Re: Qwen 3.8 27B

#536

Post by nubg »

isomorphic wrote: post #367
Casteil wrote: post #26

Earlier quoted context omitted.

I'm hoping too that they'll put out some MoE variants. Qwen3.5:122b:a10b can run about twice as fast as this 27b dense model. Edit: Like its predecessors, 3.8 seems really inclined to overthinking, and on a 27b dense model that's kind of painful. I think I'm going to stick with gemma4:26b-a3b as my go-to because it runs about 4x as fast and tends to only need a fraction of the tokens in its 'thinking' stage to get th…

"inclined to overthinking," holy cats you're not kidding! On a Mac mini M4 Pro 64GB I prompted it with "svg owl" and it thought for 17m12s, outputting 36.3KiB of thinking chatter. It did end up producing a 20.2KiB HTML+JS+SVG file with a very nice owl, including cursor-tracking animation, but it ran for more than a half hour! The MoE models are stupendously faster.

what harness did you use?

Re: Qwen 3.8 27B

#537

Post by notnullorvoid »

distrill wrote: post #528
simonw wrote: post #419

Absolutely the best pelican I've seen from a model that runs on my laptop: https://tools.simonwillison.net/markdown-svg-renderer#url=ht... Bicycle is the right shape. Pelican beak is excellent. Nice background. Most importantly, the pelican has one leg on each side of the bicycle - that's very rare. (No chain on this bicycle though - in the reasoning trace it says "already chainstay... skip chain detail; maybe a smal…

this sort of test surely only works when it's a brand new concept/prompt. like the exact same models trained newer data will surely get better at putting this together over time

Try it out with your own prompt, I suspect you'll be surprised.

Re: Qwen 3.8 27B

#539

Post by qlte »

anana_ wrote: post #492
simplyluke wrote: post #84

Earlier quoted context omitted.

I'm convinced a lot of the anti-open-weight model comments at this point are inorganic traffic - there's trillions in investor money riding on a world where these models aren't cheap commodities. Having actually used things like the recent GLM, Kimi, and Qwen I think any edge the labs have is marginal at most and actually prefer the open weight models in most day to day usage. Anthropic's recent releases are wordy to…

When stuff like this: https://doublespeed.ai/ exists I don't find that hard to believe at all, although it cuts both ways

Backed by a16z... yep, that tracks

Re: Qwen 3.8 27B

#540

Post by gr_norm »

EB66 wrote: post #448
stusmall wrote: post #436

Earlier quoted context omitted.

I'm generally extremely skeptical about a lot of the model hype that show up in comments. Except when there is an extreme mismatch the performance, quirks and quality of these things are difficult to nail down. You wouldn't know that from the comment section of every single release . I think some of these are excited, eager users always ready to hype up the new thing. The same crowd that previously would constantly p…

> I think most of it is bot driven spam by the various labs. It's hard not to notice 3 month old accounts with very strong opinions about various frontier labs and little else. I've assumed the same as well. I also assume that many of the companies developing these models engage in benchmaxxing. At my company we've developed our own internal benchmarks for evaluating LLM models as they become available. The benchmark…

> OpenAI models tend to dominate our internal benchmarks.

That's odd, since Fable seems to be the leader for the industry. Not cost-effective, but if Anthropic models get dominated by OpenAI in your internal benchmarks, this calls their validity into question. Separately, see the jagged frontier effect. [1]

I've been using GLM 5.2 at my day job (mostly Rust backend work ATM). Nothing that blows away the models from OpenAI and Anthropic, but solidly good enough to get it done. A lot of people have experienced this and the fact that an open weights model can do so is where most of the excitement comes from. Optimizing for benchmarks can only get you so far, and people are quick to criticize models that fall into it (like DeepSeek Pro V4 recently).

[1] https://mitsloan.mit.edu/ideas-made-to-matter/working-defini...

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