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Qwen3-Next

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Re: Qwen3-Next

#61

Post by matchcc »

irthomasthomas wrote: post #19

llm -m qwen3-next-80b-a3b-thinking "An ASCII of spongebob" Here's a classic ASCII art representation of SpongeBob SquarePants: .------. / o o \ | | | \___/ | \_______/ llm -m chutes/Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8 \ "An ASCII of spongebob" Here's an ASCII art of SpongeBob SquarePants: .--..--..--..--..--..--. .' \ (`._ (_) _ \ .' | '._) (_) | \ _.')\ .----..--.' / |(_.' | / .-\-. \---. \ 0| | ( O| O) | | | _…

I think there is some distillation relationship between Kimi K2 and Qwen Coder or other related other models, or same training data. I tried most of LLMs, only kimi K2 gave the exact same ASCII. kimi K2: Here’s a classic ASCII art of SpongeBob SquarePants for you:

           .--..--..--..--..--..--.
        .' \  (`._   (_)     _   \
      .'    |  '._)         (_)  |
      \ _.')\      .----..---.   /
      |(_.'  |    /    .-\-.  \  |
      \     0|    |   ( O| O) | o|
       |  _  |  .--.____.'._.-.  |
       \ (_) | o         -` .-`  |
        |    \   |`-._ _ _ _ _\ /
        \    |   |  `. |_||_|   |
        | o  |    \_      \     |     -.   .-.
        |.-.  \     `--..-'   O |     `.`-' .'
      _.'  .' |     `-.-'      /-.__   ' .-'
    .' `-.` '.|='=.='=.='=.='=|._/_ `-'.'
    `-._  `.  |________/\_____|    `-.'
       .'   ).| '=' '='\/ '=' |
       `._.`  '---------------'
               //___\   //___\
                 ||       ||
                 ||_.-.   ||_.-.
                (_.--__) (_.--__)
Enjoy your SpongeBob ASCII!

Re: Qwen3-Next

#62

Post by electroglyph »

jwr wrote: post #44

Hmm. 80B. These days I am on the lookout for new models in the 32B range, since that is what fits and runs comfortably on my MacBook Pro (M4, 64GB). I use ollama every day for spam filtering: gemma3:27b works great, but I use gpt-oss:20b on a daily basis because it's so much faster and comparable in performance.

it'll run great, it's an moe.

Re: Qwen3-Next

#63

Post by littlestymaar »

EnPissant wrote: post #41
regularfry wrote: post #39

Earlier quoted context omitted.

This isn't quite right: it'll run with the full model loaded to RAM, swapping in the experts as it needs. It has turned out in the past that experts can be stable across more than one token so you're not swapping as much as you'd think. I don't know if that's been confirmed to still be true on recent MoEs, but I wouldn't be surprised.

What you are describing would be uselessly slow and nobody does that.

AFAIK many people on /r/localLlama do pretty much that.

Re: Qwen3-Next

#64

Post by nakamoto_damacy »

matchcc wrote: post #61
irthomasthomas wrote: post #19

llm -m qwen3-next-80b-a3b-thinking "An ASCII of spongebob" Here's a classic ASCII art representation of SpongeBob SquarePants: .------. / o o \ | | | \___/ | \_______/ llm -m chutes/Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8 \ "An ASCII of spongebob" Here's an ASCII art of SpongeBob SquarePants: .--..--..--..--..--..--. .' \ (`._ (_) _ \ .' | '._) (_) | \ _.')\ .----..--.' / |(_.' | / .-\-. \---. \ 0| | ( O| O) | | | _…

I think there is some distillation relationship between Kimi K2 and Qwen Coder or other related other models, or same training data. I tried most of LLMs, only kimi K2 gave the exact same ASCII. kimi K2: Here’s a classic ASCII art of SpongeBob SquarePants for you: .--..--..--..--..--..--. .' \ (`._ (_) _ \ .' | '._) (_) | \ _.')\ .----..---. / |(_.' | / .-\-. \ | \ 0| | ( O| O) | o| | _ | .--.____.'._.-. | \ (_) | o…

For ascii to look right, not messed up, the generator has to know the width of the div in ascii characters, e.g. 80, 240, etc, so it can make sure the lines don't wrap. So how does an LLM know anything about the UI it's serving? Is it just luck? what if you ask it to draw something that like 16:9 in aspect ratio... would it know to scale it dowm so lines won't wrap? how about loss of details if it does? Also, is it as good with Unicode art? So many questions.

Re: Qwen3-Next

#65

Post by Alifatisk »

Alibaba keeps releasing gold content

I just tried Qwen3-Next-80B-A3B on Qwen chat, and it's fast! The quality seem to match Qwen3-235B-A22B. Quite impressive how they achieved this. Can't wait for the benchmarks at Artificial analysis

According to Qwen Chat, Qwen3-Next has the following limits:

Maximum context length: 262,144 tokens

Max summary generation length: 32,768 tokens

This is 2x higher on context length and 4x higher on summary generation compared to Qwen3-235B-A22B, damn

> Qwen3-Next [...] excels in ultra-long-context understanding and complex tasks

Even though their new hybrid architecture is fascinating, I think I'll continue to stick with Qwen2.5-Turbo because it's one of the few models that supports 1M tokens in context length. My use case is uploading large pdfs and ask questions across chapters

Re: Qwen3-Next

#66

Post by mmmllm »

The same week Oracle is forecasting huge data center demand and the stock is rallying. If these 10x gains in efficiency hold true then this could lead to a lot less demand for Nvidia, Oracle, Coreweave etc

Re: Qwen3-Next

#68

Post by rwoerz »

cbm-vic-20 wrote: post #49
irthomasthomas wrote: post #35

Earlier quoted context omitted.

Yes - they all do that. Actually, most attempts start well but unravel toward the end. llm -m chutes/Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8 \ "An ASCII of spongebob" Here's an ASCII art of SpongeBob SquarePants: ``` .--..--..--..--..--..--. .' \ (`._ (_) _ \ .' | '._) (_) | \ _.')\ .----..--. / |(_.' | / .-\-. \ \ 0| | ( O| O) | | _ | .--.____.'._.-. /.' ) | (_.' .-'"`-. _.-._.-.--.-. / .''. | .' `-. .-'-. .-'"`-.`-…

Ph'nglui mglw'nafh Cthulhu R'lyeh wgah'nagl fhtagn.

He is dead??

Re: Qwen3-Next

#69

Post by ls65536 »

mmmllm wrote: post #66

The same week Oracle is forecasting huge data center demand and the stock is rallying. If these 10x gains in efficiency hold true then this could lead to a lot less demand for Nvidia, Oracle, Coreweave etc

I'm not going to speculate about what might be ahead in regards to Oracle's forecasting of data center demand, but regarding the idea of efficiency gains leading to lower demand, don't you think something like Jevons paradox might apply here?
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