THE TRUE GOD-TIER MASTERPIECE: UNMATCHED QUALITY UNLEASHED

#12
by tooltd - opened

Holy shit, after a few tests I've gotta say this is the absolute best Qwen 27B I've ever used.
The results were quite surprising.
My hardware can only manage IQ4_XS Low, but it completely destroys every other IQ4_XS variant on HuggingFace.
It's the real deal.

Thanks, bro πŸ˜€

Thank you so much! ;
More are coming... but they need some cookin'

What were you testing?

Holy shit, after a few tests I've gotta say this is the absolute best Qwen 27B I've ever used.
The results were quite surprising.
My hardware can only manage IQ4_XS Low, but it completely destroys every other IQ4_XS variant on HuggingFace.
It's the real deal.

Thanks, bro πŸ˜€

Hello, I have a few observations after using IQ4_XS-Low for two days. I mainly used it with Pi coding agent.

Fable-Fusion-711 is very compliant with instructions, proactively uses tools and skills, and seems more like a top-tier model. Local models are very lazy in using tools and skills unless thoroughly instructed.

It can perform a task with a single prompt without errors, without having to repeat error correction operations multiple times. With the same prompt, output is often better than expected compared to base version or some other variants (only comparison on IQ4_XS, not on higher quantization.)

I compared it to Ornith 35B in UD-Q8_K_XL without compressing KV cache. Ornith ran faster but had significantly more errors, used more tokens, and its tool usage seemed like that of a young, careless person, while Fable-Fusion-711 was like a mature user.

DavidAU pinned discussion

Please cook UD-IQ3-XXS

@gowthamkudupudi ; the IQ2_M will meet IQ3_XXS levels. ;

Are you doing some kind of QAT + OPD for each level of quantization ? would explain the delay ;)

@jojohai
Wish I could say yes, that is an excellent idea!

@DavidAU
What am i doing wrong? standard qwen27b-mtp runs at full gpu speed, but this model uses about 80% gpu and 20%cpu or something like that... in task manager. iq_4xs quant, windows vulkan llama.cpp. Identical parameters/flags. Just same as i use for standard model. -np 1 --no-mmap --spec-type draft-mtp --spec-draft-n-max 2 --cache-type-k q8_0 --cache-type-v q8_0.
For my igpu system this means almost 2x lower speed than standard qwen27b-mtp!

Any other model on my system always uses 100%gpu with vulkan

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