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Qwen 3.8 27B

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Re: Qwen 3.8 27B

#311

Post by albedoa »

kennywinker wrote: post #266
satvikpendem wrote: post #242

Earlier quoted context omitted.

Yeah I'm sure everyone on r/cursor or in previous HN threads about Grok 4.5 or 4.6 are all unserious and insane. No one actually cares about the politics as long as the model codes well. Edit, quite interesting to see the reception to this comment compared to essentially the same type of comment I made on a Grok 4.6 benchmark HN post: https://news.ycombinator.com/item?id=49275385#49275571 It's true that Cursor gives…

This is the “Mussolini made the trains run on time” of ai hot takes. (Btw, mussolini didn’t make the trains run on time)

Also: "What do you mean everybody at this party is a Nazi? They seem uninterested in politics, and they have been so welcoming to me!"

Re: Qwen 3.8 27B

#312

Post by gaigalas »

Waiting for the MTP version to pop up on Unsloth. Speculative decoding makes a huge difference.

Been running quantized 3.6 at 110t/s on a cheap 5060Ti and quite happy with it. If 3.8 improves on it, it would be awesome.

Re: Qwen 3.8 27B

#313

Post by hypfer »

hedgehog wrote: post #303
hypfer wrote: post #163

Earlier quoted context omitted.

Yes to both. The thing is that I can either use the q8 context, or have not enough context window, so I just live with whatever degradation there is. The same can be said about the IQ4_NL. I would not go any lower though. As for the draft count, indeed that depends on what you do with it, but for coding, reverse engineering and that kind of stuff it does pay off in my testing, though 5 is really pushing it, but the 4…

Same, I have one workload where on 3.6 drafting 6 tokens is the fastest setting.

I wonder if we could take a page out of the Solar power book and do MPPT but for draft count. Constantly sweep through possible values to find the best result for the current conditions.

Though it might turn out that that doesn't offer any benefits. Has it been tried yet?

___

EDIT:

LLM pointed me towards this thing I'm not going to read

https://arxiv.org/abs/2512.11280

"AdaSD: Adaptive Speculative Decoding for Efficient Language Model Inference"

Some higher level nerd please go have a look at that. I have important meetings and golf classes to attend.

Re: Qwen 3.8 27B

#315

Post by kamranjon »

LeBit wrote: post #190
Almondsetat wrote: post #132

The $1500 Intel B70 with 32GB of VRAM can run this model at max context with good performance, btw. If you don't want to drop $5-10k for running DeepSeek this is your best budget option for local refactor/small scale dev help

I understand the B70 is a bargain vs AMD and especially nVidia offerings, but to me it feels like I would be buying something that would feel too limited in less than a year. 48G would be much more confortable. And I know the 96G nVidia cards are selling for over 10k$. The future can’t arrive fast enough!

You can buy two b60s for $1300 right now (650 each) if you want a total of 48gb. Intel recently raised the price on all of their gpu's except the b60 series, so they are currently the best deal per gb I think.

Re: Qwen 3.8 27B

#316

Post by apitman »

kanemcgrath wrote: post #301
apitman wrote: post #291

Earlier quoted context omitted.

Running it on 2x3060 now. Works pretty well but VRAM is tight . 4bit quants. 1x128k context, 8bit KV, MTP on.

whats the tok/s you get on that. I have heard a few claims of around 30-50 with mtp, but for how cheap the setup is I am surprised I don't hear more about 3060 stacks so I assume there has to be some catch.

I used GPT-5.6 Sol high to optimize it, and it claimed it was getting 50. I'm seeing ~40 on my goto smoketest: "Make me a vector add in CUDA".

Funny side note. It successfully one shot the program, but it wasn't able to run it because there literally wasn't enough VRAM left to allocate CUDA memory. Watching it try to debug that was fascinating. I'm pretty sure it would have killed the llama-server (and thus itself) if it hadn't been running in a separate container.

Re: Qwen 3.8 27B

#317

Post by jLaForest »

satvikpendem wrote: post #242
altruios wrote: post #235

Earlier quoted context omitted.

[flagged]

Yeah I'm sure everyone on r/cursor or in previous HN threads about Grok 4.5 or 4.6 are all unserious and insane. No one actually cares about the politics as long as the model codes well. Edit, quite interesting to see the reception to this comment compared to essentially the same type of comment I made on a Grok 4.6 benchmark HN post: https://news.ycombinator.com/item?id=49275385#49275571 It's true that Cursor gives…

i care about not financially supporting a person that is actively trying to disenfranchise me, why is that a difficult concept for some people? that not everyone is motivated exclusively by financial profit? is moral bankruptcy so pervasive that some people assume it is unanimous?

Re: Qwen 3.8 27B

#319

Post by hedgehog »

skrebbel wrote: post #178
satvikpendem wrote: post #161

As usual, the Jinja templates are messed up so use this [0] to reduce or turn off thinking, fix tool calling, keep a 100% KV cache hit rate, etc. [0] https://huggingface.co/froggeric/Qwen-Fixed-Chat-Templates

I'd love to understand this more. Are you saying the Qwen team spends their very impressive human and compute resources on publishing these amazing models and then botches the chat template with mundane bugs? Like maybe I just misunderstand what's the hard part but wouldn't you assume that people who can put together an impressive model can also write a proper jinja chat template for it?

Yes, I was fixing issues piecemeal until I found the froggeric template, I've had to fix I think one issues with that one but it's better.

Re: Qwen 3.8 27B

#320

Post by ndriscoll »

hypfer wrote: post #313
hedgehog wrote: post #303

Earlier quoted context omitted.

Same, I have one workload where on 3.6 drafting 6 tokens is the fastest setting.

I wonder if we could take a page out of the Solar power book and do MPPT but for draft count. Constantly sweep through possible values to find the best result for the current conditions. Though it might turn out that that doesn't offer any benefits. Has it been tried yet? ___ EDIT: LLM pointed me towards this thing I'm not going to read https://arxiv.org/abs/2512.11280 "AdaSD: Adaptive Speculative Decoding for Effici…

Don't you just need to occasionally try n+1 for your current setting? Then record acceptance rates. The nature of the thing is that if you try n, you already have a good sampling of how well m works for all m<n, right?
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